Search results for: Parkinson's disease

Authors: Petra Balla, Gabor Manhertz, Akos Antal

Abstract:

Nowadays spinal deformities are very frequent problems among teenagers. Scheuermann disease is a one dimensional deformity of the spine, but it has prevalence over 11% of the children. A traditional technology, the moiré method was used by us for screening and diagnosing this type of spinal deformity. A LabVIEW program has been developed to evaluate the moiré pictures of patients with Scheuermann disease. Two different solutions were tested in this computer program, the extreme and the inflexion point calculation methods. Effects using these methods were compared and according to the results both solutions seemed to be appropriate. Statistical results showed better efficiency in case of the extreme search method where the average difference was only 6,09⁰.

Keywords: Spinal deformity, picture evaluation, moiré method, Scheuermann disease, curve detection, moiré topography.

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Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

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Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, medial temporal atrophy, LOO Cycle.

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Authors: Rong Zhou, Shun’ich Kaneko, Fumio Tanaka, Miyuki Kayamori, Motoshige Shimizu

Abstract:

In this paper, we propose a robust disease detection method, called adaptive orientation code matching (Adaptive OCM), which is developed from a robust image registration algorithm: orientation code matching (OCM), to achieve continuous and site-specific detection of changes in plant disease. We use two-stage framework for realizing our research purpose; in the first stage, adaptive OCM was employed which could not only realize the continuous and site-specific observation of disease development, but also shows its excellent robustness for non-rigid plant object searching in scene illumination, translation, small rotation and occlusion changes and then in the second stage, a machine learning method of support vector machine (SVM) based on a feature of two dimensional (2D) xy-color histogram is further utilized for pixel-wise disease classification and quantification. The indoor experiment results demonstrate the feasibility and potential of our proposed algorithm, which could be implemented in real field situation for better observation of plant disease development.

Keywords: Cercospora Leaf Spot (CLS), Disease detection, Image processing, Orientation Code Matching (OCM), Support Vector Machine (SVM).

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Authors: P. Pongsumpun

Abstract:

Herpes zoster is a disease that manifests as a dermatological condition. The characteristic of this disease is an irritating skin rash with blisters. This is often limited to one side of body. From the data of Herpes zoster cases in Thailand, we found that age structure effects to the transmission of this disease. In this study, we construct the age structural model of Herpes zoster in Thailand. The local stability analysis of this model is given. The numerical solutions are shown to confirm the analytical results.

Keywords: Age structural model, Herpes zoster, local stability, Numerical solution.

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Authors: C. Gallottini, W. Di Mari, A. Amaddeo, K. Barbaro, A. Dolci, G. Dolci, L. Gallottini, G. Barraco, S. Eramo

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A group of 10 dogs (group A) with Periodontal Disease in the third stage, were subjected to regenerative therapy of periodontal tissues, by use of nano hydroxy apatite (NHA). These animals induced by general anesthesia, where treated by ultrasonic scaling, root planning, and at the end by a mucogingival flap in which it was applied NHA. The flap was closed and sutured with simple steps. Another group of 10 dogs (group B), control group, was treated only by scaling and root planning. No patient was subjected to antibiotic therapy. After three months, a check was made by inspection of the oral cavity, radiography and bone biopsy at the alveolar level. Group A showed a total restitutio ad integrum of the periodontal structures, and in group B still mild gingivitis in 70% of cases and 30% of the state remains unchanged. Numerous experimental studies both in animals and humans have documented that the grafts of porous hydroxyapatite are rapidly invaded by fibrovascular tissue which is subsequently converted into mature lamellar bone tissue by activating osteoblast. Since we acted on the removal of necrotic cementum and rehabilitating the root tissue by polishing without intervention in the ligament but only on anatomical functional interface of cement-blasts, we can connect the positive evolution of the clinical-only component of the cement that could represent this perspective, the only reason that Periodontal Disease become a Cement Disease, while all other clinical elements as nothing more than a clinical pathological accompanying.

Keywords: Nanoidroxiaphatite, Parodontal Disease, Rigenerative Therapy.

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Authors: Rujira Kongnuy, Puntani Pongsumpun, I-Ming Tang

Abstract:

Dengue fever is an important human arboviral disease. Outbreaks are now reported quite often from many parts of the world. The number of cases involving pregnant women and infant cases are increasing every year. The illness is often severe and complications may occur. Deaths often occur because of the difficulties in early diagnosis and in the improper management of the diseases. Dengue antibodies from pregnant women are passed on to infants and this protects the infants from dengue infections. Antibodies from the mother are transferred to the fetus when it is still in the womb. In this study, we formulate a mathematical model to describe the transmission of this disease in pregnant women. The model is formulated by dividing the human population into pregnant women and non-pregnant human (men and non-pregnant women). Each class is subdivided into susceptible (S), infectious (I) and recovered (R) subclasses. We apply standard dynamical analysis to our model. Conditions for the local stability of the equilibrium points are given. The numerical simulations are shown. The bifurcation diagrams of our model are discussed. The control of this disease in pregnant women is discussed in terms of the threshold conditions.

Keywords: Dengue disease, local stability, mathematical model, pregnancy.

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Authors: K. Muthukannan, P. Latha

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In addition to environmental parameters like rain, temperature diseases on crop is a major factor which affects production quality & quantity of crop yield. Hence disease management is a key issue in agriculture. For the management of disease, it needs to be detected at early stage. So, treat it properly & control spread of the disease. Now a day, it is possible to use the images of diseased leaf to detect the type of disease by using image processing techniques. This can be achieved by extracting features from the images which can be further used with classification algorithms or content based image retrieval systems. In this paper, color image is used to extract the features such as mean and standard deviation after the process of region cropping. The selected features are taken from the cropped image with different image size samples. Then, the extracted features are taken in to the account for classification using Fuzzy Inference System (FIS).

Keywords: Image Cropping, Classification, Color, Fuzzy Rule, Feature Extraction.

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Authors: T. Khenenou, M. Melizi, H. Benzaoui

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The study of morphometric and histologic evolutions of the Bursa of Fabricus during 27 weeks of post-hashing age, realized on 88 subjects of broiler chicken they permitted to collect information about the morpho-histological aspect according to their post-hashing age; showed the size and the weight of the Bursa of Fabricius which reach their maximum between the 10th and the 11th week of age and the physiologic involution phenomena. These variations are in close relationship to the sexual maturity. These results can be used in the diagnosis of viral disease such as the Gumboro disease, Marek disease.

Keywords: Broiler chicken, bursa of Fabricius, Morphohistology, post-hashing evolution.

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Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

Abstract:

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, Speech Emotion Recognition, longitudinal biomarker, machine learning.

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Authors: Rujijan Vichivanives, Kittiya Poonsilp, Canasanan Wanavijit

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This research aims to create mobile tools to analyze rice disease quickly and easily. The principle of object-oriented software engineering and objective-C language were used for software development methodology and the principle of decision tree technique was used for analysis method. Application users can select the features of rice disease or the color appears on the rice leaves for recognition analysis results on iOS mobile screen. After completing the software development, unit testing and integrating testing method were used to check for program validity. In addition, three plant experts and forty farmers have been assessed for usability and benefit of this system. The overall of users’ satisfaction was found in a good level, 57%. The plant experts give a comment on the addition of various disease symptoms in the database for more precise results of the analysis. For further research, it is suggested that image processing system should be developed as a tool that allows users search and analyze for rice diseases more convenient with great accuracy.

Keywords: Rice disease, analysis system, mobile application, iOS operating system.

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Authors: P. Pongsumpun

Abstract:

Leptospirosis occurs worldwide (except the poles of the earth), urban and rural areas, developed and developing countries, especially in Thailand. It can be transmitted to the human by rats through direct and indirect ways. Human can be infected by either touching the infected rats or contacting with water, soil containing urine from the infected rats through skin, eyes and nose. The data of the people who are infected with this disease indicates that most of the patients are adults. The transmission of this disease is studied through mathematical model. The population is separated into human and rat. The human is divided into two classes, namely juvenile and adult. The model equation is constructed for each class. The standard dynamical modeling method is then used for analyzing the behaviours of solutions. In addition, the conditions of the parameters for the disease free and endemic states are obtained. Numerical solutions are shown to support the theoretical predictions. The results of this study guide the way to decrease the disease outbreak.

Keywords: Adult human, juvenile human, leptospirosis, mathematical model.

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Authors: Zhongxu Chen, Jun Yang, Heyue Mao, Xiaoyu Zheng

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Hemorrhage Disease of Grass Carp (HDGC) is a kind of commonly occurring illnesses in summer, and the extremely high death rate result in colossal losses to aquaculture. As the complex connections among each factor which influences aquiculture diseases, there-s no quit reasonable mathematical model to solve the problem at present.A BP neural network which with excellent nonlinear mapping coherence was adopted to establish mathematical model; Environmental factor, which can easily detected, such as breeding density, water temperature, pH and light intensity was set as the main analyzing object. 25 groups of experimental data were used for training and test, and the accuracy of using the model to predict the trend of HDGC was above 80%. It is demonstrated that BP neural network for predicating diseases in HDGC has a particularly objectivity and practicality, thus it can be spread to other aquiculture disease.

Keywords: Aquaculture, Hemorrhage Disease of Grass Carp, BP Neural Network

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Authors: Rozilawati Binti Dollah, Masaki Aono

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Classifying biomedical literature is a difficult and challenging task, especially when a large number of biomedical articles should be organized into a hierarchical structure. In this paper, we present an approach for classifying a collection of biomedical text abstracts downloaded from Medline database with the help of ontology alignment. To accomplish our goal, we construct two types of hierarchies, the OHSUMED disease hierarchy and the Medline abstract disease hierarchies from the OHSUMED dataset and the Medline abstracts, respectively. Then, we enrich the OHSUMED disease hierarchy before adapting it to ontology alignment process for finding probable concepts or categories. Subsequently, we compute the cosine similarity between the vector in probable concepts (in the “enriched" OHSUMED disease hierarchy) and the vector in Medline abstract disease hierarchies. Finally, we assign category to the new Medline abstracts based on the similarity score. The results obtained from the experiments show the performance of our proposed approach for hierarchical classification is slightly better than the performance of the multi-class flat classification.

Keywords: Biomedical literature, hierarchical text classification, ontology alignment, text mining.

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Authors: Kasra Afsahi, Maryam Soheilifar

Abstract:

Cerebrovascular accident (CVA) is a neurological side effect of COVID-19 disease wit high rate in pandemics. Effect of COVID-19 disease on disorder is unclear. In this cohort, patients with COVID-19 disease were assessed. 60 CVA cases were assessed in a referral hospital in 2020. The major factor was mortality and the cases were those with and without death. The groups were compared for all features about mortality in the patients with COVID-19 and CVA. Totally 23 out of 60 cases (38.3%) were expired. In univariate analysis there was significant association for death by ischemic heart disease (P = 0.015), high-severity stroke (P = 0.012), high C-reactive protein (CRP) (P = 0.001), high ESR (P = 0.009), pleural effusion (P = 0.005), pericardial effusion (P = 0.027), cardiomegaly (P = 0.005), ground glass opacity (P = 0.001), and consolidation (P = 0.001). Among these factors, there was significant association only for CRP (P = 0.001) and consolidation (P = 0.003) in multivariate analysis. Mortality in the cases with COVID-19-related CVA is one-third and it has relationship to elevated CRP and finding the consolidation in the computerized tomography scan of the lungs.

Keywords: COVID-19, stroke, prognosis, C-reactive protein, CRP.

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Authors: B. R. O. Omidiwura, A. F. Agboola, E. A. Iyayi

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Pure form of L-Dopa is used to enhance muscular development, fat breakdown and suppress Parkinson disease in humans. However, the L-Dopa in mucuna seed, when present with other antinutritional factors, causes nutritional disorders in monogastric animals. Information on the utilisation of pure L-Dopa in monogastric animals is scanty. Therefore, effect of L-Dopa on growth performance and carcass characteristics in broiler chickens was investigated. Two hundred and forty one-day-old chicks were allotted to six treatments, which consisted of a positive control (PC) with standard energy (3100Kcal/Kg) and negative control (NC) with high energy (3500Kcal/Kg). The rest 4 diets were NC+0.1, NC+0.2, NC+0.3 and NC+0.4% L-Dopa, respectively. All treatments had 4 replicates in a completely randomized design. Body weight gain, final weight, feed intake, dressed weight and carcass characteristics were determined. Body weight gain and final weight of birds fed PC were 1791.0 and 1830.0g, NC+0.1% L-Dopa were 1827.7 and 1866.7g and NC+0.2% L-Dopa were 1871.9 and 1910.9g respectively, and the feed intake of PC (3231.5g), were better than other treatments. The dressed weight at 1375.0g and 1357.1g of birds fed NC+0.1% and NC+0.2% L-Dopa, respectively, were similar but better than other treatments. Also, the thigh (202.5g and 194.9g) and the breast meat (413.8g and 410.8g) of birds fed NC+0.1% and NC+0.2% L-Dopa, respectively, were similar but better than birds fed other treatments. The drum stick of birds fed NC+0.1% L-Dopa (220.5g) was observed to be better than birds on other diets. Meat to bone ratio and relative organ weights were not affected across treatments. L-Dopa extract, at levels tested, had no detrimental effect on broilers, rather better bird performance and carcass characteristics were observed especially at 0.1% and 0.2% L-Dopa inclusion rates. Therefore, 0.2% inclusion is recommended in diets of broiler chickens for improved performance and carcass characteristics.

Keywords: Broilers, Carcass characteristics, L-Dopa, performance.

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Authors: N. A. Samat, D. F. Percy

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The main aim of this study is to describe and introduce a method of numerical analysis in obtaining approximate solutions for the SIR-SI differential equations (susceptible-infectiverecovered for human populations; susceptible-infective for vector populations) that represent a model for dengue disease transmission. Firstly, we describe the ordinary differential equations for the SIR-SI disease transmission models. Then, we introduce the numerical analysis of solutions of this continuous time, discrete space SIR-SI model by simplifying the continuous time scale to a densely populated, discrete time scale. This is followed by the application of this numerical analysis of solutions of the SIR-SI differential equations to the estimation of relative risk using continuous time, discrete space dengue data of Kuala Lumpur, Malaysia. Finally, we present the results of the analysis, comparing and displaying the results in graphs, table and maps. Results of the numerical analysis of solutions that we implemented offers a useful and potentially superior model for estimating relative risks based on continuous time, discrete space data for vector borne infectious diseases specifically for dengue disease. 

Keywords: Dengue disease, disease mapping, numerical analysis, SIR-SI differential equations.

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Authors: Yang Zhang, Jian He

Abstract:

Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper presents sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for CHD prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, coronary heart disease, ECG, electrocardiogram, ResNet, sliding window.

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Authors: Somorjeet Sharma Shamurailatpam, Rabindra Das, A. Suchitra Devi

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Computer and video display users might complain about Asthenopia, burning, dry eyes etc. The management of dry eyes is often not in the lines of severity. Following systematic evaluation and grading, dry eye disease is one condition that can be practiced at all levels of ophthalmic care. In the present study, different spectrum causing dry eye and prevalence of dry eye disease in computer users of Manipur, India are determined with 600 individuals (300 cases and 300 control). Individuals between 15 and 50 years who used computers for more than 3 hrs a day for 1 year or more were included. Tear break up time (TBUT) and Schirmer’s test were conducted. It shows that 33 (20.4%) out of 164 males and 47 (30.3%) out of 136 females have dry eye. Possible explanation for the observed result is discussed.

Keywords: Asthenopia, computer vision syndrome, dry eyes, Schirmer’s test, tear breakup time.

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Authors: Rujira Kongnuy, Puntani Pongsumpun, I-Ming Tang

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Mathematical models can be used to describe the dynamics of the spread of infectious disease between susceptibles and infectious populations. Dengue fever is a re-emerging disease in the tropical and subtropical regions of the world. Its incidence has increased fourfold since 1970 and outbreaks are now reported quite frequently from many parts of the world. In dengue endemic regions, more cases of dengue infection in pregnancy and infancy are being found due to the increasing incidence. It has been reported that dengue infection was vertically transmitted to the infants. Primary dengue infection is associated with mild to high fever, headache, muscle pain and skin rash. Immune response includes IgM antibodies produced by the 5th day of symptoms and persist for 30-60 days. IgG antibodies appear on the 14th day and persist for life. Secondary infections often result in high fever and in many cases with hemorrhagic events and circulatory failure. In the present paper, a mathematical model is proposed to simulate the succession of dengue disease transmission in pregnancy and infancy. Stability analysis of the equilibrium points is carried out and a simulation is given for the different sets of parameter. Moreover, the bifurcation diagrams of our model are discussed. The controlling of this disease in infant cases is introduced in the term of the threshold condition.

Keywords: Dengue infection, equilibrium states, maternalantibodies, pregnancy and infancy.

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Authors: Nebi Gedik

Abstract:

Regardless of age or gender, cardiovascular illnesses are a serious health concern because of things like poor eating habits, stress, a sedentary lifestyle, hard work schedules, alcohol use, and weight. It tends to happen suddenly and has a high rate of recurrence. Machine learning models can be implemented to assist healthcare systems in the accurate detection and diagnosis of cardiovascular disease (CVD) in patients. Improved heart failure prediction is one of the primary goals of researchers using the heart disease dataset. The purpose of this study is to identify the feature or features that offer the best classification prediction for CVD detection. The support vector machine classifier is used to compare each feature's performance. It has been determined which feature produces the best results.

Keywords: Cardiovascular disease, feature extraction, supervised learning, support vector machine.

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Authors: H. C. Chinwenyi, H. D. Ibrahim, J. O. Adekunle

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The incubation period is defined as the time from infection with a microorganism to development of symptoms. In this research, two disease models: one with incubation period and another without incubation period were studied. The study involves the use of a  mathematical model with a single incubation period. The test for the existence and stability of the disease free and the endemic equilibrium states for both models were carried out. The fourth order Runge-Kutta method was used to solve both models numerically. Finally, a computer program in MATLAB was developed to run the numerical experiments. From the results, we are able to show that the endemic equilibrium state of the model with incubation period is locally asymptotically stable whereas the endemic equilibrium state of the model without incubation period is unstable under certain conditions on the given model parameters. It was also established that the disease free equilibrium states of the model with and without incubation period are locally asymptotically stable. Furthermore, results from numerical experiments using empirical data obtained from Nigeria Centre for Disease Control (NCDC) showed that the overall population of the infected people for the model with incubation period is higher than that without incubation period. We also established from the results obtained that as the transmission rate from susceptible to infected population increases, the peak values of the infected population for the model with incubation period decrease and are always less than those for the model without incubation period.

Keywords: Asymptotic stability, incubation period, Routh-Hurwitz criterion, Runge Kutta method.

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Authors: Jae-Yeon Song, Seung-Yerl Lee, Kyu-Yeul Wang, Byung-Soo Kim, Sang-Seol Lee, Seong-Seob Shin, Jae-Young Choi, Chong Ho Lee, Jeahyun Park, Duck-Jin Chung

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In this paper, we propose disease diagnosis hardware architecture by using Hypernetworks technique. It can be used to diagnose 3 different diseases (SPECT Heart, Leukemia, Prostate cancer). Generally, the disparate diseases require specified diagnosis hardware model for each disease. Using similarities of three diseases diagnosis processor, we design diagnosis processor that can diagnose three different diseases. Our proposed architecture that is combining three processors to one processor can reduce hardware size without decrease of the accuracy.

Keywords: Diagnosis processor, Hypernetworks, Leukemia, Mask, Prostate cancer, SPECT Heart data

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Authors: R. Kongnuy, E. Naowanich

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In this paper we develop and analyze the model for the spread of Leptospirosis by age group in Thailand, between 1997 and 2010 by using mathematical modeling and computer simulation. Leptospirosis is caused by pathogenic spirochetes of the genus Leptospira. It is a zoonotic disease of global importance and an emerging health problem in Thailand. In Thailand, leptospirosis is a reportable disease, the top three age groups are 23.31% in 35-44 years olds group, 22.76% in 25-34 year olds group, 17.60% in 45-54 year olds group from reported leptospirosis between 1997 and 2010, with a peak in 35-44 year olds group. Our paper, the Leptosipirosis transmission by age group in Thailand is studied on the mathematical model. Some analytical and simulation results are presented.

Keywords: Age Group, Equilibrium State, Leptospirosis, Mathematical Modeling.

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Authors: Sadek Makhlouf, Hassan M. Nouh

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Bone hydatidosis is an infection in worldwide distribution. Although there is no evidence in literature on Bone Hydatid disease in Libya, we tried to present the first Epidemiological study of this disease in Eastern Libya through retrospective study from 1995 to 2013. Our data were collected from 3 hospitals in Eastern Libya particularly the sheep-raising areas with total number of musculoskeletal infection cases of two thousand one hundred ninety four (2,194). There were five (5) five cases of bone infection, four (4) of it have been diagnosed after more than three (3) months.  Our study is comparable to other international study but this type of bone infection need further studies for effective control strategies for all dogs to avoid serious complications that might happened from the delay in diagnosing this type of disease.

Keywords: Bone infection, Hydatidosis, Eastern Libya, Sheep-raising areas.

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Authors: Negar Khezri, Golnaz Yaghoubnezhadzanganeh, Amirreza Attarzadeh

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Type 2 Diabetes (T2DM) and Alzheimer's disease (AD) are two main health problems influencing millions of people in the world. Neuron loss and synaptic impairment that interfere with cognition and memory cause for the behavioral indications of AD. While it is now accepted that insulin has central neuromodulatory purpose, it was contemplated for many years that brain is insusceptible to insulin, involving its function in memory and learning, which are impaired in AD. The common characteristics of both AD and T2D are impaired insulin signaling, oxidative stress, the excitation of inflammatory pathways and unqualified glucose metabolism. This review summarizes how the recognition of these mechanisms may lead to the development of alternative therapeutic approaches. Here we summarize how the recognition of these mechanisms may lead to the development of alternative therapeutic approaches.

Keywords: Alzheimer’s disease, diabetes, insulin resistance, neurodegenerative.

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Authors: Piyush Samant, Ravinder Agarwal

Abstract:

Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: Complementary and alternative medicine, Iridology, iris, feature extraction, classification, disease prediction.

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Authors: Ahsan Bin Tufail, Ali Abidi, Adil Masood Siddiqui, Muhammad Shahzad Younis

Abstract:

An early and accurate detection of Alzheimer's disease (AD) is an important stage in the treatment of individuals suffering from AD. We present an approach based on the use of structural magnetic resonance imaging (sMRI) phase images to distinguish between normal controls (NC), mild cognitive impairment (MCI) and AD patients with clinical dementia rating (CDR) of 1. Independent component analysis (ICA) technique is used for extracting useful features which form the inputs to the support vector machines (SVM), K nearest neighbour (kNN) and multilayer artificial neural network (ANN) classifiers to discriminate between the three classes. The obtained results are encouraging in terms of classification accuracy and effectively ascertain the usefulness of phase images for the classification of different stages of Alzheimer-s disease.

Keywords: Biomedical image processing, classification algorithms, feature extraction, statistical learning.

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Authors: E. Vári, K. Máriás

Abstract:

The research focused on the effects of previous cropping and fertilizers on the LAI, rhythm of the dry matter, leaf disease intensity and amount of yield. Long term field experiments’ results proved that the previous crop fundamentally determines size, rate and dynamics of the dry matter formation in the spring time vegetation period. The LAI index and crop results of winter wheat can be influenced mainly by raising the fertilizer amount. N fertilization has an outstanding role in the changes in leaf area index (LAI), weight of dry matter and yield of winter wheat. According to our results, the interaction effect of leaf area index, weight of dry matter and fertilization resulted in the maximum yield in biculture and triculture.

Keywords: Crop rotation, Leaf Area Index, leaf disease of winter wheat.

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Authors: K. Jyothi, T. S. Mohamed Saleem, L. Vineela, C. Gopinath, K. B. Yadavender Reddy

Abstract:

Objective: Acute coronary syndrome is a clinical condition encompassing ST segments elevation myocardial infraction, Non ST segment is elevation myocardial infraction and un stable angina is characterized by ruptured coronary plaque, stress and myocardial injury. Angina pectoris is a pressure like pain in the chest that is induced by exertion or stress and relived with in the minute after cessation of effort or using sublingual nitroglycerin. The present research was undertaken to study the drug utilization pattern of antiplatelet drugs for the ischemic heart disease in a tertiary care hospital. Method: The present study is retrospective drug utilization study and study period is 6months. The data is collected from the discharge case sheet of general medicine department from medical department Rajiv Gandhi institute of medical sciences, Kadapa. The tentative sample size fixed was 250 patients. Out of 250 cases 19 cases was excluded because of unrelated data. Results: A total of 250 prescriptions were collected for the study according to the inclusion criteria 233 prescriptions were diagnosed with ischemic heart disease 17 prescriptions were excluded due to unrelated information. out of 233 prescriptions 128 are male (54.9%) and 105 patients are were female (45%). According to the gender distribution, the prevalence of ischemic heart disease in males are 90 (70.31%) and females are 39 (37.1%). In the same way the prevalence of ischemic heart disease along with cerebrovascular disease in males are 39 (29.6%) and females are 66 (62.6%). Conclusion: We found that 94.8% of drug utilization of antiplatelet drugs was achieved in the Rajiv Gandhi institute of medical sciences, Kadapa from 2011-2012.

Keywords: Angina pectoris, aspirin, clopidogrel, myocardial infarction.

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Authors: Asmaa M. Hussein, Amr Wassal, Ahmed Farouk Al-Sadek, A. F. Abd El-Rahman

Abstract:

In this study, a multivariate analysis of potato spectroscopic data was presented to detect the presence of brown rot disease or not. Near-Infrared (NIR) spectroscopy (1,350-2,500 nm) combined with multivariate analysis was used as a rapid, non-destructive technique for the detection of brown rot disease in potatoes. Spectral measurements were performed in 565 samples, which were chosen randomly at the infection place in the potato slice. In this study, 254 infected and 311 uninfected (brown rot-free) samples were analyzed using different advanced statistical analysis techniques. The discrimination performance of different multivariate analysis techniques, including classification, pre-processing, and dimension reduction, were compared. Applying a random forest algorithm classifier with different pre-processing techniques to raw spectra had the best performance as the total classification accuracy of 98.7% was achieved in discriminating infected potatoes from control.

Keywords: Brown rot disease, NIR spectroscopy, potato, random forest.

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