Search results for: diabetes diagnosis

Authors: Mbonigaba Swale

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Malaria is an infection or disease caused by parasites (Plasmodium Falciparum — causes severe Malaria, plasmodium Vivax, Plasmodium Ovale, and Plasmodium Malariae), transmitted by bites of infected anopheles (female) mosquitoes to humans. These vectors comprise of two types in Africa, particularly in Uganda, i.e. anopheles fenestus and Anopheles gambaie (‘example Anopheles arabiensis,,); feeds on man inside the house mainly at dusk, mid-night and dawn and rests indoors and makes them effective transmitters (vectors) of the disease. People in both urban and rural areas have consistently become prone to repetitive attacks of malaria, causing a lot of deaths and significantly increasing the poverty levels of the rural poor. Malaria is a national problem; it causes a lot of maternal pre-natal and antenatal disorders, anemia in pregnant mothers, low birth weights for the newly born, convulsions and epilepsy among the infants. Cumulatively, it kills about one million children every year in sub-Saharan Africa. It has been estimated to account for 25-35% of all outpatient visits, 20-45% of acute hospital admissions and 15-35% of hospital deaths. Uganda is the leading victim country, for which Rakai and Masaka districts are the most affected. So, it is not clear whether these abhorrent situations and episodes of recurrences and failure to cure from the disease are a result of poor diagnosis, prescription and dosing, treatment habits and compliance of the patients to the drugs or the ethical domain of the stake holders in relation to the main stream methodology of malaria management. The research is aimed at offering an alternative approach to manage and deal absolutely with problem by using a knowledge based software model of Artificial Intelligence (Al) that is capable of performing common-sense and cognitive reasoning so as to take decisions like the human brain would do to provide instantaneous expert solutions so as to avoid speculative simulation of the problem during differential diagnosis in the most accurate and literal inferential aspect. This system will assist physicians in many kinds of medical diagnosis, prescribing treatments and doses, and in monitoring patient responses, basing on the body weight and age group of the patient, it will be able to provide instantaneous and timely information options, alternative ways and approaches to influence decision making during case analysis. The computerized system approach, a new model in Uganda termed as “Software Aided Treatment” (SAT) will try to change the moral and ethical approach and influence conduct so as to improve the skills, experience and values (social and ethical) in the administration and management of the disease and drugs (combination therapy and generics) by both the patient and the health worker.

Keywords: knowledge based software, management, treatment, diagnosis

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Gadiri Sabiha

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Introduction: Current allergy diagnostic tools using Multiplex technology have made it possible to increase the efficiency of the search for specific IgE. This opportunity is provided by the newly developed “Alex Biochip”, consisting of a panel of 282 allergens in native and molecular form, a CCD inhibitor, and the potential for detecting cross-reactive allergens. We evaluated the performance of this technology in detecting cross-reactivity in previously explored patients. Material/Method: The sera of 39 patients presenting sensitization and polysensitization profiles were explored. The search for specific IgE is carried out by the Alex ® IgE Biochip, and the results are analyzed by nature and by molecular family of allergens using specific software. Results/Discussion: The analysis gave a particular profile of cross-reactivity allergens: 33% for the Ole e1 family, 31% for NPC2, 26% for storage proteins, 20% for Tropomyosin, 10% for LTPs, 10% for Arginine Kinase and 10% for Uteroglobin CCDs were absent in all patients. The “Ole e1” allergen is responsible for a pollen-pollen cross allergy. The storage proteins found and LTP are not species-specific, causing cross-pollen-food allergy. The nDer p2 of the NPC2 family is responsible for cross-reactivity between mite species. Conclusion: The cross-reactivities responsible for mixed syndromes at diagnosis in our patients were dominated by pollen-pollen and pollen-food syndromes. They allow the identification of severity factors linked to the prognosis and the best-adapted immunotherapy.

Keywords: specific IgE, allergy, cross reactivity, molecular allergens

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Authors: P. S. Percin, O. Inanli, S. Karakaya

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Bitter melon (Momordica charantia) is a medicinal vegetable, which is used traditionally to remedy diabetes. Bitter melon contains several classes of primary and secondary metabolites. In traditional Turkish medicine bitter melon is used for wound healing and treatment of peptic ulcers. Nowadays, bitter melon is used for the treatment of diabetes and ulcerative colitis in many countries. The main constituents of bitter melon, which are responsible for the anti-diabetic effects, are triterpene, protein, steroid, alkaloid and phenolic compounds. In this study total phenolics, total carotenoids and β-carotene contents of mature and immature bitter melons were determined. In addition, in vitro α-amylase and α-glucosidase activities of mature and immature bitter melons were studied. Total phenolic contents of immature and mature bitter melon were 74 and 123 mg CE/g bitter melon respectively. Although total phenolics of mature bitter melon was higher than that of immature bitter melon, this difference was not found statistically significant (p > 0.05). Carotenoids, a diverse group of more than 600 naturally occurring red, orange and yellow pigments, play important roles in many physiological processes both in plants and humans. The total carotenoid content of mature bitter melon was 4.36 fold higher than the total carotenoid content of immature bitter melon. The compounds that have hypoglycaemic effect of bitter melon are steroidal saponins known as charantin, insulin-like peptides and alkaloids. α-Amylase is one of the main enzymes in human that is responsible for the breakdown of starch to more simple sugars. Therefore, the inhibitors of this enzyme can delay the carbohydrate digestion and reduce the rate of glucose absorption. The immature bitter melon extract showed α-amylase and α-glucosidase inhibitory activities in vitro. α-Amylase inhibitory activity was higher than that of α-glucosidase inhibitory activity when IC50 values were compared. In conclusion, the present results provide evidence that aqueous extract of bitter melon may have an inhibitory effect on carbohydrate breakdown enzymes.

Keywords: bitter melon, in vitro antidiabetic activity, total carotenoids, total phenols

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Authors: Isabel Cristina Ortiz Trujillo, Lina Maria Martinez Sanchez, Felipe Hernández Restrepo, Daniel Gallego Gonzalez, Natalia Vargas Grisales, Camilo Andrés Agudelo Vélez

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Chorioamnionitis, is a pregnancy infection, causes different fetal and maternal symptoms. Streptococcus agalactiae present in the normal vaginal microflora of some women, favouring its abnormal multiplication during pregnancy, causing perinatal morbidity and mortality. Objective. Describe the clinical and epidemiological profile of the patients with diagnosis of clinical chorioanmionitis. Methodology. Descriptive, cross-sectional study. The population was patients with diagnosis of clinical chorioanmionitis. The information was taken from the medical records. The research was approved by the Ethics Committee. We used the program SPSS ® version 17.0 (SPSS Inc; Chicago, Illinois, USA) for the information analysis, descriptive statistics were used. Results. 78 patients in total with clinical chorioamnionitis, with a mean age of 26.3 ±5, 8 years old, the 69.2% primigravid women. 2.6% of women had positive culture for Streptococcus agalactiae in urine sample during current pregnancy and 30.7% had received some kind of antibiotics during current pregnancy. The 57.7% had 37 to 40 weeks of gestation in the current pregnancy it was calculated more frequently by ultrasound (66.7% in first quarter, 11.5% in the second and 1.9% in the third). In a 60.3% way of termination of pregnancy was vaginal and a 35.9 percent were caesarean section. Among the women in the study, a 30.8% had premature rupture of membranes. Conclusion. The chorioamnionitis continues to be an important cause of antibiotic use during pregnancy or labour and the decision to do a caesarean, with highest percentage in pregnancies-preterm and preterm premature rupture of membranes.

Keywords: chorioamnionitis, Streptococcus agalactiae, pregnancy complications, infectious

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Authors: Badino Manuel, Farias María Alejandra

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Anxiety and depression are considered the main mental health issues found in people with substance-related disorders. Furthermore, substance-related disorders, anxiety-related and depressive disorders are among the leading causes of disability and are associated with increased mortality. The co-occurrence of substance-related disorders and these mental health conditions affect the accuracy in diagnosis, treatment plan, and recovery process. The aim is to describe the prevalence of anxiety and depression in patients with substance-related disorders in a mental health service in Córdoba, Argentina. A descriptive cross-sectional study was conducted among patients with substance-related disorders (N=305). Anxiety and depression were assessed using the Patient Health Questionnaire-4 (PHQ-4) during the period from December 2021 to March 2022. For a total of 305 participants, 71,8% were male, 25,6% female and 2,6% non-binary. As regards marital status, 51,5% were single, 21,6% as a couple, 5,9% married, 15,4% separated and 5,6% divorced. In relation to education status, 26,2% finished university, 56,1% high school, 16,4% only primary school and 1,3% no formal schooling. Regarding age, 10,8% were young, 84,3% were adults, and 4,9% were elderly. In-person treatment represented 64,6% of service users, and 35,4% were conducted through teleconsultation. 15,7% of service users scored 3 or higher for anxiety, and 32,1% scored 3 or higher for depression in the PHQ-4. 13,1% obtained a score of 3 or higher for both anxiety and depression. It is recommended to identify anxiety and depression among patients with substance-related disorders to improve the quality of diagnosis, treatment, and recovery. It is suggested to apply PHQ-4, PHQ-9 within the protocol of care for these patients.

Keywords: addiction, anxiety, depression, mental health

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Authors: Mehwish Asghar

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Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

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Authors: Nura Lawal, Lawal Suleiman Bilbis, Rabiu Aliyu Umar, Anas A. Sabir

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Metabolic syndrome (MS) a high-risk condition involving obesity, dyslipidemia, hypertension, and diabetes mellitus is prevalent in Nigeria. The study aims to formulate an antioxidant-rich nutraceutical from locally available foodstuff (onion, garlic, ginger, tomato, lemon, palm oil, watermelon seeds) and investigate their effects on blood pressure, body weight, serum glucose, lipid profile, insulin and oxidative stress markers in salt-induced rats. The rats were placed on 8% salt diet for 6 weeks and then supplementation and treatment with nutraceutical and nifedipine in the presence of salt diet for additional 4 weeks. Feeding rats with salt diet for 6 weeks increased blood pressure and body weight of the salt-loaded rats relative to control. Significant (P < 0.001) increase in serum blood glucose and lipid profile, and the decrease in high-density lipoprotein-cholesterol (HDL-C) was observed in salt-loaded rats as compared with control. Both supplementation and treatment (nifedipine) lowered the blood pressure but the only supplementation lowered the body weight. Supplementation with nutraceutical resulted in significant (P < 0.001) decrease in the serum blood glucose, lipid profile, malonyldialdehyde (MDA), insulin levels, insulin resistance, and increased HDL-C and antioxidant indices. The percentage protection against atherogenesis was 76.5±2.13%. There is strong positive correlation between blood pressure, body weight and serum blood glucose, lipid profile, markers of oxidative stress and strong negative correlation with HDL-C and antioxidant status. The results suggest that the nutraceuticals are useful in reversing most of the component of metabolic syndrome and might be beneficial in the treatment of patients with metabolic syndrome.

Keywords: metabolic syndrome, hypertension, diabetes mallitus, obesity

Procedia PDF Downloads 241

Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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Authors: Tomoko Fukuyama, Osamu Senbu

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Prestressed concrete is used a lot in infrastructures such as roads or bridges. However, poor grout filling and PC steel corrosion are currently major issues of prestressed concrete structures. One of the problems with nondestructive corrosion detection of PC steel is a plastic pipe which covers PC steel. The insulative property of pipe makes a nondestructive diagnosis difficult; therefore a practical technology to detect these defects is necessary for the maintenance of infrastructures. The goal of the research is a development of an electrochemical technique which enables to detect internal defects from the surface of prestressed concrete nondestructively. Ideally, the measurements should be conducted from the surface of structural members to diagnose non-destructively. In the present experiment, a prestressed concrete member is simplified as a layered specimen to simulate a current path between an input and an output electrode on a member surface. The specimens which are layered by mortar and the prestressed concrete constitution materials (steel, polyethylene, stainless steel, or galvanized steel plates) were provided to the alternating current impedance measurement. The magnitude of an applied electric field was 0.01-volt or 1-volt, and the frequency range was from 106 Hz to 10-2 Hz. The frequency spectrums of impedance, which relate to charge reactions activated by an electric field, were measured to clarify the effects of the material configurations or the properties. In the civil engineering field, the Nyquist diagram is popular to analyze impedance and it is a good way to grasp electric relaxation using a shape of the plot. However, it is slightly not suitable to figure out an influence of a measurement frequency which is reciprocal of reaction time. Hence, Bode diagram is also applied to describe charge reactions in the present paper. From the experiment results, the alternating current impedance method looks to be applicable to the insulative material measurement and eventually prestressed concrete diagnosis. At the same time, the frequency spectrums of impedance show the difference of the material configuration. This is because the charge mobility reflects the variety of substances and also the measuring frequency of the electric field determines migration length of charges which are under the influence of the electric field. However, it could not distinguish the differences of the material thickness and is inferred the difficulties of prestressed concrete diagnosis to identify the amount of an air void or a layer of corrosion product by the technique.

Keywords: capacitance, conductance, prestressed concrete, susceptance

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Authors: Olga Blagova, Yuliya Osipova, Evgeniya Kogan, Alexander Nedostup

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Purpose: to quantify the value of various clinical, laboratory and instrumental signs in the diagnosis of myocarditis in comparison with morphological studies of the myocardium. Methods: in 100 patients (65 men, 44.7±12.5 years) with «idiopathic» arrhythmias (n = 20) and dilated cardiomyopathy (DCM, n = 80) were performed 71 endomyocardial biopsy (EMB), 13 intraoperative biopsy, 5 study of explanted hearts, 11 autopsy with virus investigation (real-time PCR) of the blood and myocardium. Anti-heart antibodies (AHA) were also measured as well as cardiac CT (n = 45), MRI (n = 25), coronary angiography (n = 47). The comparison group included of 50 patients (25 men, 53.7±11.7 years) with non-inflammatory heart diseases who underwent open heart surgery. Results. Active/borderline myocarditis was diagnosed in 76.0% of the study group and in 21.6% of patients of the comparison group (p < 0.001). The myocardial viral genome was observed more frequently in patients of comparison group than in study group (group (65.0% and 40.2%; p < 0.01. Evaluated the diagnostic value of noninvasive markers of myocarditis. The panel of anti-heart antibodies had the greatest importance to identify myocarditis: sensitivity was 81.5%, positive and negative predictive value was 75.0 and 60.5%. It is defined diagnostic value of non-invasive markers of myocarditis and diagnostic algorithm providing an individual assessment of the likelihood of myocarditis is developed. Conclusion. The greatest significance in the diagnosis of latent myocarditis in patients with 'idiopathic' arrhythmias and DCM have AHA. The use of complex of noninvasive criteria allows estimate the probability of myocarditis and determine the indications for EMB.

Keywords: myocarditis, "idiopathic" arrhythmias, dilated cardiomyopathy, endomyocardial biopsy, viral genome, anti-heart antibodies

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Authors: A. Erragh, K. Amanzoui, M. Elharit, H. Salem, M. Ababneh, K. Elfakhr, S. Kalouch, A. Chlilek

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Guillain-Barre syndrome (GBS) is the most common form of acute polyradiculoneuritis (PRNA). It is a medical emergency in pediatrics that requires rapid diagnosis and immediate assessment of the severity criteria for the implementation of appropriate treatment. Retrospective, descriptive study in 24 patients under the age of 18 who presented with GBS between September 2017 and July 2021 and were hospitalized in the multipurpose pediatric intensive care unit of the Abderrahim EL Harouchi children's hospital in Casablanca. The average age was 7.91 years, with extremes ranging from 18 months and 14 years and a male predominance of 75%. After a prodromal event, most often infectious (80%) and a free interval of 12 days on average, 2 types of motor disorders begin either hypo or arereflectic flaccid paralysis of the lower limbs (45.8%) or flaccid quadriplegia hypo or arereflectic (54.2%). During GBS, the most formidable complication is respiratory distress, which can occur at any time. In our study, respiratory impairment was observed in 70.8% of cases. In addition, other signs of severity, such as swallowing disorders (75%) and dysautonomic disorders (8.33%), were also observed, which justified care in the intensive care unit for all of our patients. The use of invasive ventilation was necessary in 76.5% of cases, and specific treatments based on immunoglobulins were administered in all our patients. Despite everything, the death rate remains high (25%) and is mainly due to complications related to hospitalization. Guillain Barré syndrome is, therefore, a pediatric emergency that requires rapid diagnosis and immediate assessment of severity criteria for the implementation of appropriate treatment.

Keywords: guillain barre syndrome, emergency, children, medical

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Authors: Zainab Elazab, Azhar Aziz

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Background: Spontaneous Splenic artery pseudoaneurysm rupture is a rare condition which is potentially life threatening, if not detected and managed early. We report a case of abdominal pain with intraperitoneal free fluid, which turned out to be spontaneous rupture of a splenic artery pseudoaneurysm, and was treated with arterial embolization. Case presentation: A 28-year old, previously healthy male presented to the ED with a history of sudden onset upper abdominal pain and fainting attack. The patient denied any history of trauma or prior similar attacks. On examination, the patient had tachycardia and a low-normal BP (HR 110, BP 106/66) but his other vital signs were normal (Temp. 37.2, RR 18 and SpO2 100%). His abdomen was initially soft with mild tenderness in the upper region. Blood tests showed leukocytosis of 12.3 X109/L, Hb of 12.6 g/dl and lactic acid of 5.9 mmol/L. Ultrasound showed trace of free fluid in the perihepatic and perisplenic areas, and a splenic hypoechoic lesion. The patient remained stable; however, his abdomen became increasingly tender with guarding. We made a provisional diagnosis of a perforated viscus and the patient was started on IV fluids and IV antibiotics. An erect abdominal x-ray did not show any free air under the diaphragm so a CT abdomen was requested. Meanwhile, bedside ultrasound was repeated which showed increased amount of free fluid, suggesting intra-abdominal bleeding as the most probable etiology for the condition. His CT abdomen revealed a splenic injury with multiple lacerations, a focal intrasplenic enhancing area on venous phase scan (suggesting a pseudoaneurysm with associated splenic intraparenchymal, sub capsular and perisplenic hematomas). Free fluid in the subhepatic and intraperitoneal regions along the small bowel was also detected. Angiogram was done which confirmed a diagnosis of pseudoaneurysm of intrasplenic arterial branch, and angio-embolization was done to control the bleeding. The patient was later discharged in good condition with a surgery follow-up. Conclusion: Splenic artery pseudoaneurysm rupture is a rare cause of abdominal pain which should be considered in any case of abdominal pain with intraperitoneal bleeding. Early management is crucial as it carries a high mortality. Bedside ultrasound is a useful tool to help for early diagnosis of such cases.

Keywords: abdominal pain, pseudo aneurysm, rupture, splenic artery

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Authors: Abdollah Sobhani, Hossein Vaseghi-Dodaran

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Proteomics is defined as the study of the component of a cell, tissue and biological fluid. This technique has the potential to identify protein biomarkers of a disease states. In this study which was performed on bovine ovarian follicular cysts (BOFC), eight proteins are over expressed in BOFC that these proteins could be useful biomarkers for BOFC. The difference between serum proteome pattern cows affected by postpartum endometritis with healthy cows revealed that concentrations orosomucoid was decreased in endometritis. The comparison proteome of brucella abortus between laboratory adapted strains and clinical isolates could be useful to better understand this disease and vaccine development. Proteomics experiments identified new proteins and pathways that may be important in future hypothesis-driven studies of glucocorticoid-induced immunosuppression. Understanding the molecular mechanisms of effective parameters on male fertility is essential for obtaining high reproductive efficiency by decreasing cost and time. The investigations on proteome of high fertility spermatozoa indicated that expression of some proteins such as casein kinase 2 (CKII) prime poly peptide and tyrosine kinase in high fertility spermatozoa was higher compared to low fertility spermatozoa. Also, some evidence has indicated that variation in protein types and amounts in seminal fluid regulates fertility indexes in dairy bull. In conclusion, proteomics is a useful technique for discovering drugs, vaccine development, and diagnosis disease by biomarkers and improvement of reproduction efficiency.

Keywords: proteomics, reproduction, biomarker, immunity

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Authors: Kay-Anne Haykal, Issack Biyong

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The post-traumatic stress disorder (PTSD) rises from exposure to a traumatic event and appears by a persistent experience of this event. Several psychiatric co-morbidities are associated with PTSD and include mood disorders, anxiety disorders, and substance abuse. The main objective was to compare the criteria for PTSD according to the literature to those used to diagnose a patient in a francophone hospital and to check the correspondence of these two criteria. 700 medical charts of admitted patients on the medicine or psychiatric unit at the Montfort Hospital were identified with the following diagnoses: major depressive disorder, bipolar disorder, anxiety disorder, substance abuse, and PTSD for the period of time between April 2005 and March 2006. Multiple demographic criteria were assembled. Also, for every chart analyzed, the PTSD criteria, according to the Manual of Mental Disorders (DSM) IV were found, identified, and grouped according to pre-established codes. An analysis using the receiver operating characteristic (ROC) method was elaborated for the study of data. A sample of 57 women and 50 men was studied. Age was varying between 18 and 88 years with a median age of 48. According to the PTSD criteria in the DSM IV, 12 patients should have the diagnosis of PTSD in opposition to only two identified in the medical charts. The ROC method establishes that with the combination of data from PTSD and depression, the sensitivity varies between 0,127 and 0,282, and the specificity varies between 0,889 and 0,917. Otherwise, if we examine the PTSD data alone, the sensibility jumps to 0.50, and the specificity varies between 0,781 and 0,895. This study confirms the presence of an underdiagnosed and treated PTSD that causes severe perturbations for the affected individual.

Keywords: post-traumatic stress disorder, co-morbidities, diagnosis, mental health disorders

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Authors: L. José, S. Vieira, E. Melo, A. R. Pinheiro

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Objectives: This study aims to characterize the stroke profile and the health care provided for people with a stroke in Luanda, Angola. Methods: A prospective longitudinal study was conducted at two Health centers, from March to November 2023, enrolling stroke patients. Data was gathered using a survey created by the researchers and validated by a health panel of experts from Angola. The analysis focused on demographic and stroke characteristics, as well as the care provided. Ethical approval and informed consent were obtained. Results: Preliminary results of a total of 186 patients are described, 122 from a Central Acute Care Hospital, with a mean age of 51.3±14.35 years old, a BMI of 26.7±4.15 kg/m2, 41% male, and 64 patients from a Rehabilitation Center, with 55.6±11.55 years old, a BMI of 27.0±3.8 kg/m2, 53% male. Ischemic stroke was reported as the most representative type in both centers (71.3% and 70.3%, respectively), though 100% of patients had no imaging diagnosis confirmation, neither data about the subtype was given. For patients admitted to the Hospital, discharge occurred before rehabilitation, and no follow-up was possible. No rehabilitation care was delivered in the first 7 days after the stroke. In the Rehabilitation Center, patient’s rehabilitation started in the late subacute phase, after a mean of 171.8±11.5 days. Conclusions: Stroke diagnosis lacks imaging confirmation, which is decisive for proper treatment, and rehabilitation starts during the late subacute phase, which is too late considering the international guidelines and the best window of opportunity for neuroplasticity and recovery. These results highlight the urgent need for the definition of Stroke-directed Health Care Policies in Angola.

Keywords: stroke, personalized health care, functional recovery, quality of life, health policies

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Authors: Rashida Suleiman, Asamoah Jnr. Boakye, Suleiman Ahmed Ibn Ahmed

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In recent years, there has been an enormous success in discoveries of scientific knowledge in medicine coupled with the advancement of technology. Despite all these successes, diagnoses and treatment of diseases have become complex. MYCIN is a groundbreaking illustration of a clinical decision support system (CDSS), which was developed to assist physicians in the diagnosis and treatment of bacterial infections by providing suggestions for antibiotic regimens. MYCIN was one of the earliest expert systems to demonstrate how CDSSs may assist human decision-making in complicated areas. Relevant databases were searched using google scholar, PubMed and general Google search, which were peculiar to clinical decision support systems. The articles were then screened for a comprehensive overview of the functionality, consultative style and statistical usage of MYCIN, a clinical decision support system. Inferences drawn from the articles showed some usage of MYCIN for problem-based learning among clinicians and students in some countries. Furthermore, the data demonstrated that MYCIN had completed clinical testing at Stanford University Hospital following years of research. The system (MYCIN) was shown to be extremely accurate and effective in diagnosing and treating bacterial infections, and it demonstrated how CDSSs might enhance clinical decision-making in difficult circumstances. Despite the challenges MYCIN presents, the benefits of its usage to clinicians, students and software developers are enormous.

Keywords: clinical decision support system, MYCIN, diagnosis, bacterial infections, support systems

Procedia PDF Downloads 137

Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

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Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

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Authors: Nasibullina A., Leonov D.

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The ultrasonography method is actively used for the early diagnosis of various le-sions in the human body, including the mammary gland. The incidence of breast cancer has increased by more than 20%, and mortality by 14% since 2008. The correctness of the diagnosis often directly depends on the qualifications and expe-rience of a diagnostic medical sonographer. That is why special attention should be paid to the practical training of future specialists. Anatomical phantoms are ex-cellent teaching tools because they accurately imitate the characteristics of real hu-man tissues and organs. The purpose of this work is to create a breast phantom for practicing ultrasound diagnostic skills in grayscale and elastography imaging, as well as ultrasound-guided biopsy sampling. We used silicone-like compounds ranging from 3 to 17 on the Shore scale hardness units to simulate soft tissue and lesions. Impurities with experimentally selected concentrations were added to give the phantom the necessary attenuation and reflection parameters. We used 3D modeling programs and 3D printing with PLA plastic to create the casting mold. We developed a breast phantom with inclusions of varying shape, elasticity and echogenicity. After testing the created phantom in B-mode and elastography mode, we performed a survey asking 19 participants how realistic the sonograms of the phantom were. The results showed that the closest to real was the model of the cyst with 9.5 on the 0-10 similarity scale. Thus, the developed breast phantom can be used for ultrasonography, elastography, and ultrasound-guided biopsy training.

Keywords: breast ultrasound, mammary gland, mammography, training phantom, tissue-mimicking materials

Procedia PDF Downloads 88

Authors: Hassan Ali Abood Nassrullah, Jabbar Fadeel Mahdi, Mohammed Salih Mahdi Alkurdi, Ali Al Mousawi, Saad Ibrahim Al-Ghabban, Abdul Amir H. Kadhum, Ahmed Al-Amiery

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Background: Q fever is a zoonotic disease characterized by its clinical polymorphism and can present acutely as fever, pneumonia, hepatitis, and chronically as infective endocarditis, arthritis, osteomyelitis, or hepatitis. Objective: The aim of this study is To estimate the prevalence of cases of Q fever in hospitalized febrile patients in Imam Al Hussain Teaching Medical City in Karbala. Methods: One hundred patients with pyrexia were admitted to the medical ward from 1st August to 31st December 2019. Serological procedures fortified by Enzyme-linked Immunosorbent Assay test. Patients were considered to have acute Q fever when the specific antibodies (IgM and IgG) of phase II of Coxiella burnetii were positive. Results: The mean age of the patients was 35.05±12.93 years; females constituted 60% of them. Eighteen patients (18%) showed positive results for IgM, a lower proportion (13% n=13) had positive IgG levels, and 9% showed equivocal results. Statistical analysis revealed a significant association between positive IgM levels of the female gender and in patients consuming unpasteurized milk. One patient (female aged 60 years) died in the hospital, while all other patients were discharged well. Two female patients were pregnant, and one of them had an abortion. Conclusions: Q fever is more common in febrile patients. The study indicates that this disease should not be overlooked in the differential diagnosis of acute fever. Serological testing should be performed in all patients with acute febrile illness with an unsettling diagnosis.

Keywords: antibodies, frequency, immunoglobulin IgM, Q fever

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Authors: Munkhtuul G., Bolortsetseg Z., Lutzul M., Sugar N., Nyamdorj D., Nomundari B., Zesemdorj O., Erdenebayar N., Lkhagvasuren T. S., Munkhbayarlakh S., Bayasgalan T. Uurtuya S. H.

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Background: Elevated serum uric acid (SUA) levels are observed in metabolic and cardiovascular conditions as an early predictor of metabolic syndrome (MS). Hyperuricemia, characterised by high uric acid levels in serum, increases the risk of developing MS by 1.6 times. Being overweight and obese significantly contributes to developing MS and cardiovascular disorders. In Mongolia, the prevalence of overweight and obesity is reaching 48.8% among individuals aged 15 to 49 years, indicating a potential surge in the incidence of MS, cardiovascular disorders, diabetes mellitus, and gout.Objective: This study aimed to determine the SUA levels in men diagnosed with MS and investigate the factors influencing these levels.Methods: A total of 119 men aged 30-60, who underwent preventive examinations and resided in Ulaanbaatar city, were included in the study. The criteria established by the International Diabetes Federation (IDF), American Heart Association (AHA), and the National Heart, Lung, and Blood Institute (NHLBI) were employed to define metabolic syndrome. Hyperuricemia was defined as SUA levels ≥7 mg/dL. Dietary intake was evaluated through the 24-hour recall method.Results: The study revealed that the prevalence of MS among the participants was 42.9% (n=51), with hyperuricemia observed in 16.8% (n=20) of the individuals. Among men diagnosed with MS, 21.3% (n=10) exhibited hyperuricemia. The mean SUA levels were as follows: 4.7±0.8 mg/dL in the healthy group, 5.9±1.1 mg/dL in men without MS but presenting central obesity, and 6.2±1.3 mg/dL in men with MS. After adjusting for age and body mass index (BMI), a positive correlation was observed between SUA levels and triglycerides (β=0.93) as well as lipid accumulation product (LAP) (β=0.92) in men with MS. In the central obesity group, SUA levels exhibited a positive correlation with triglycerides (β=0.91), visceral adiposity index (VAI) (β=0.73), LAP (β=0.92), and cardiometabolic index (CMI) (β=0.69). The risk of hyperuricemia increased by 3.29 times with elevated triglycerides and 3.53 times with an increased LAP.Conclusion: The findings indicate that abdominal fat accumulation, as indicated by elevated triglyceride levels and LAP, is associated with increased SUA levels in men with MS. However, no significant relationship was observed between SUA levels and dietary intake.

Keywords: central obesity, obesity, triglycerides, hyperuricemia

Procedia PDF Downloads 57

Authors: Mannan Mridha, Usama Gazay, Kosovare V. Aslani, Hugo Linder, Alice Ravizza, Carmelo de Maria

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In most developing countries, although the vast majority of the people are living in the rural areas, the qualified medical doctors are not available there. Health care workers and paramedics, called village doctors, informal healthcare providers, are largely responsible for the rural medical care. Mishaps due to wrong diagnosis and inappropriate medication have been causing serious suffering that is preventable. While innovators have created many devices, the vast majority of these technologies do not find applications to address the needs and conditions in low-resource settings. The primary motive is to address the acute lack of affordable medical technologies for the poor people in low-resource settings. A low cost smart medical device that is portable, battery operated and can be used at any point of care has been developed to detect breathing rate, electrocardiogram (ECG) and arterial pulse rate to improve diagnosis and monitoring of patients and thus improve care and safety. This simple and easy to use smart medical device can be used, managed and maintained effectively and safely by any health worker with some training. In order to empower the health workers and village doctors, our device is being further developed to integrate with ICT tools like smart phones and connect to the medical experts wherever available, to manage the serious health problems.

Keywords: e-health for low resources settings, health awareness education, improve patient care and safety, smart and affordable medical device

Procedia PDF Downloads 191

Authors: Grace McCambridge, Alanna Keady, Madhur Agrawal, Dequina Nicholas Alvarado, Barbara Nikolajczyk, Leena Panneerseelan-Bharath

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Age is a non-modifiable risk factor for the inflammation that underlies pathologies such as type 2 diabetes mellitus (T2DM). Inflammation, as indicated by circulating cytokines, rises in aging, but mechanisms that promote this ‘inflammaging’ remain poorly defined. Furthermore, downstream consequences of inflammaging, including the development of an inflammatory profile that predicts comorbidities like T2DM, remain speculative. We tested the possibility that natural aging-associated changes in autophagy, a process that is compromised in both aging and T2DM, regulates inflammatory profiles in older subjects. Our data showed that circulating CD4⁺ T cells from older compared to younger subjects have (i) defects in autophagy; (ii) higher mitochondria accumulation; (iii) a failure to metabolically shift from oxidative phosphorylation to anaerobic glycolysis upon αCD3/CD28 activation; (iv) more reactive oxygen species (ROS) accumulation; and (v) a cytokine profile that recapitulates the Th17 profile that predicts T2DM. ROS scavenging in cells from older subjects restored mitochondrial mass and membrane potential (indicators of improved autophagy) and reduced Th17 cytokines to amounts made by T cells from younger subjects. Knock-down of the autophagy protein Atg3 in T cells from younger subjects increased mitochondrial accumulation and Th17 cytokines. To begin translating these findings to clinical practice, we showed that physiological concentrations of the diabetes drug metformin (100 µM) added in vitro enhanced autophagy, prevented mitochondria and ROS accumulation, increased anaerobic glycolysis, and decreased Th17 cytokines in activated CD4⁺ T cells from older subjects. Metformin therefore improves autophagy and multiple downstream pro-inflammatory mechanisms CD4⁺ T cells from older subjects. We conclude that autophagy improvement ameliorates the development of a T2DM-predictive Th17 profile in aging, and thus holds promise for delay or prevention of aging-associated metabolic decline.

Keywords: autophagy, mitochondrial turnover, ROS, glycolysis

Procedia PDF Downloads 161

Authors: Abdulkader Helwan

Abstract:

Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

Procedia PDF Downloads 501

Authors: Manal Kamel, Sara Maher, Hanan El Baz, Faten Salah, Omar Sayyouh, Zeinab Demerdash

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In the recent COVID 19 pandemic, experts of public health have emphasized testing, tracking infected people, and tracing their contacts as an effective strategy to reduce the spread of the virus. Development of rapid and sensitive diagnostic assays to replace reverse transcription polymerase chain reaction (RT-PCR) is mandatory..Our innovative test strip relying on the application of nanoparticles conjugated to recombinant nanobodies for SARS-COV-2 spike protein (S1) & angiotensin-converting enzyme 2 (that is responsible for the virus entry into host cells) for rapid detection of SARS-COV-2 spike protein (S1) in saliva or sputum specimens. Comparative tests with RT-PCR will be held to estimate the significant effect of using COVID 19 nanobodies for the first time in the development of lateral flow test strip. The SARS-CoV-2 S1 (3 ng of recombinant proteins) was detected by our developed LFIA in saliva specimen of COVID-19 Patients No cross-reaction was detected with Middle East respiratory syndrome coronavirus (MERS-CoV) or SARS- CoV antigens..Our developed system revealed 96 % sensitivity and 100% specificity for saliva samples compared to 89 % and 100% sensitivity and specificity for nasopharyngeal swabs. providing a reliable alternative for the painful and uncomfortable nasopharyngeal swab process and the complexes, time consuming PCR test. An increase in testing compliances to be expected.

Keywords: COVID 19, diagnosis, LFIA, nanobodies, ACE2

Procedia PDF Downloads 133

Authors: Daudi S. Simbeye, Mbazingwa E. Mkiramweni

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Plant diseases have the potential to drastically diminish the quantity and quality of agricultural products. Guava (Psidium guajava), sometimes known as the apple of the tropics, is one of the most widely cultivated fruits in tropical regions. Monitoring plant health and diagnosing illnesses is an essential matter for sustainable agriculture, requiring the inspection of visually evident patterns on plant leaves and fruits. Due to minor variations in the symptoms of various guava illnesses, a professional opinion is required for disease diagnosis. Due to improper pesticide application by farmers, erroneous diagnoses may result in economic losses. This study proposes a method that uses artificial intelligence (AI) to detect and classify the most widespread guava plant by comparing images of its leaves and fruits to datasets. ESP32 CAM is responsible for data collection, which includes images of guava leaves and fruits. By comparing the datasets, these image formats are used as datasets to help in the diagnosis of plant diseases through the leaves and fruits, which is vital for the development of an effective automated agricultural system. The system test yielded the most accurate identification findings (99 percent accuracy in differentiating four guava fruit diseases (Canker, Mummification, Dot, and Rust) from healthy fruit). The proposed model has been interfaced with a mobile application to be used by smartphones to make a quick and responsible judgment, which can help the farmers instantly detect and prevent future production losses by enabling them to take precautions beforehand.

Keywords: early identification, guava plants, fruit diseases, deep learning

Procedia PDF Downloads 73

Authors: Nihad Chakri, Btissam El Amrani, Faouzi Berrada, Halima Jounaid, Fouad Amraoui

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In the context of the increasing water resource scarcity in Morocco in recent years, the use of unconventional resources has become imperative. Although efforts have been made in the field of sanitation in urban areas, rural areas, due to their specificities, such as scattered dwellings and limited accessibility, suffer from a lack of basic infrastructure. This work focuses on replicating the Faculty of Sciences Ain Chock (FSAC) model for the treatment and reuse of wastewater from a peri-urban traditional hammam in Casablanca, specifically in the municipality of Dar Bouazza. This initiative is part of the Eco-Hammam project, which aims to minimize the negative impacts of traditional hammams in terms of irrational and uncontrolled consumption of water and wood energy resources. To achieve this, a comprehensive environmental diagnosis of all hammams in the municipality of Dar Bouazza, our study site, has been undertaken. Then, a feasibility study is also conducted to assess the possibility of replicating the FSAC mini-station to treat the wastewater of the selected pilot hammam, namely, My Yacoub II.

Keywords: water resource scarcity, unconventional resources, sanitation, per-urban areas, rural areas, basic infrastructure, replication, reuse of wastewater, traditional hammam, Casablanca, Municipality of Dar Bouazza, negative impacts, environmental diagnosis, feasibility study, pilot hammam, My Yacoub II

Procedia PDF Downloads 58

Authors: Albina V. Moskvicheva, Gevorg G. Kazarian, Anna R. Valeeva, Marina A. Efimova, Malik N. Mukminov, Eduard A. Shuralev, Rustam Kh. Ravilov, Kamil S. Khaertynov

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Improving the early diagnosis of tuberculosis and solving a number of problems associated with the differential diagnosis of Mycobacterium bovis infection, nonspecific tuberculin reactions caused by sensitization of the body by non-tuberculosis mycobacteria, is urgent. The filtrates and extracts of M. bovis cell surface components are promising antigens with diagnostic potential. The purpose of this study was to isolate and characterize antigenic proteins and determine the dominant M. bovis antigens recognized by the humoral immune system. The mycobacterial cells were homogenized on FastPrep-24. Gel-filtration chromatography was used to fractionate the lysates of cell surface component extracts and proteins isolated from M. bovis culture supernatant. The separated fractions were analyzed using two-dimensional gel electrophoresis followed by determination of antigen serological activity using immunoblot with specific hyperimmune rabbit blood serum. As a result of electrophoretic separation of components by molecular weight, 23 antigen fractions were obtained. Analysis of densitograms showed that the fractions contained two zones of antigens with pronounced serological activity, corresponding to molecular weights of 28 and 21 kDa. The high serological activity of the 28 kDa antigen was established by immunoblot using hyperimmune blood sera. Separated and characterized by M. bovis specific antigen with a molecular weight of 28 kDa was added to the collection of specific marker antigens for M. bovis.

Keywords: antigen, gel-filtration chromatography, immunoblot, Mycobacterium bovis

Procedia PDF Downloads 133

Authors: Manjusha Choudhary

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Objective: Cassia occidentalis Linn. belongs to Family Caesalpiniaceae is a common weed scattered from the foothills of Himalayas to West Bengal, South India, Burma, and Sri Lanka. It is used widely in folklore medicine in India as laxative, expectorant, analgesic, anti-malarial, hepatoprotective, relaxant, anti-inflammatory and antidiabetic. The present study was carried out to investigate the hypoglycaemic and hypolipidemic activities of ethanolic extract of Cassia occidentalis stem bark. Methods: Stem bark extract of Cassia occidentalis (SBCO) was administered orally at 250 and 500 mg/kg doses to normal and streptozotocin (STZ) induced type-2 diabetic mice. Various parameters like fasting blood glucose (FBG) level, serum cholesterol, high density lipoprotein (HDL) cholesterol, triglycerides (TG), total protein, urea, creatinine, serum glutamate oxaloacetate transaminase (SGOT), serum glutamate pyruvate transaminase (SGPT) levels and physical parameters like change in body weight, food intake, water intake were performed for the evaluation of antidiabetic effects. Results: Both the doses of extract caused a marked decrease in FBG levels in STZ induced type 2 diabetic mice. Administration of SBCO led to the decrease in the blood glucose, food intake, water intake, organ weight, SGOT, SGPT levels with significant value and increased the levels of TG, HDL cholesterol, creatinine, cholesterol, total protein with a significant value (p < 0.05-0.01). The decrease in body weight induced by STZ was restored to normal with a significant value (p < 0.01) at both doses. Conclusion: Present study reveals that SBCO possess potent hypoglycaemic and hypolipidemic activities and supports the folklore use of the stem bark of plant as antidiabetic agent.

Keywords: Cassia occidentalis, diabetes, folklore, herbs, hypoglycemia, streptozotocin

Procedia PDF Downloads 402

Authors: Vichai Tienthavorn

Abstract:

Background: Recently, the patients of non-communicable diseases (NCDs) are increasing in Thailand; especially hypertension and diabetes. Hypertension and Diabetes patients were found to be of 3.7 million in 2008. The varieties of human behaviors have been extensively changed in health. Hence, Thai Government has a policy to reduce NCDs. Generally, primary care plays an important role in treatment using medical process. However, NCDs patients have not been decreased. Objectives: This study not only reduce the patient and mortality rate but also increase the quality of life, could apply in different areas and propose to be the national policy, effectively for a long term operation. Methods: Here we report that primary health care (PHC), which is a primary process to screening, rapidly seek the person's risk. The screening tool of the study was Vichai's 7 color balls model, the medical education tool to transfer knowledge from student health team to community through health volunteers, creating community engagement in terms of social participation. It was found that people in community were realized in their health and they can evaluate the level of risk using this model. Results: Projects implementation (2015) in Nong Lom Health Center in Phayao (target group 15-65 years, 2529); screening hypertension coveraged 99.01%, risk group (light green) was decreased to normal group (white) from 1806 to 1893, significant severe patient (red) was decreased to moderate (orange) from 10 to 5. Health Program in behaving change with best practice of 3Es (Eating, Exercise, Emotion) and 3Rs (Reducing tobacco, alcohol, obesity) were applied in risk group; and encourage strictly medication, investigation in severe patient (red). Conclusion: This is the first demonstration of knowledge transfer to community engagement by student, which is the sustainable education in PHC.

Keywords: non-communicable disease, surveillance control and prevention systems, community engagement, primary health care

Procedia PDF Downloads 248