Search results for: hospital ward

Authors: S.Jerald Jeba Kumar, M.Madheswaran

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The structure of retinal vessels is a prominent feature, that reveals information on the state of disease that are reflected in the form of measurable abnormalities in thickness and colour. Vascular structures of retina, for implementation of clinical diabetic retinopathy decision making system is presented in this paper. Retinal Vascular structure is with thin blood vessel, whose accuracy is highly dependent upon the vessel segmentation. In this paper the blood vessel thickness is automatically detected using preprocessing techniques and vessel segmentation algorithm. First the capture image is binarized to get the blood vessel structure clearly, then it is skeletonised to get the overall structure of all the terminal and branching nodes of the blood vessels. By identifying the terminal node and the branching points automatically, the main and branching blood vessel thickness is estimated. Results are presented and compared with those provided by clinical classification on 50 vessels collected from Bejan Singh Eye hospital..

Keywords: Diabetic retinopathy, Binarization, SegmentationClinical Decision Support Systems.

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Authors: İ. Kıyak, G. Gökmen

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Using of natural lighting has come into prominence in constructed buildings, especially in last ten years, under scope of energy efficiency. Natural lighting methods are one of the methods that aim to take advantage of day light in maximum level and decrease using of artificial lighting. Increasing of day light amount in buildings by using suitable methods will give optimum result in terms of comfort and energy saving when the daylight-artificial light integration is ensured with a suitable control system. Using of natural light in places that require lighting will ensure energy saving in great extent. With this study, it is aimed to save energy used for purpose of lighting. Under this scope, lighting of a scanning laboratory of a hospital was realized by using a lighting automation containing natural and artificial lighting. In natural lighting, light pipes were used and in artificial lighting, dimmable power LED modules were used. Necessity of lighting was followed with motion sensors. The lighting automation containing natural and artificial light was ensured with fuzzy logic control. At the scanning laboratory where this application was realized, energy saving in lighting was obtained.

Keywords: Daylight transfer, fuzzy logic controller, light pipe, Power LED.

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Authors: Novita Verayanti Manalu, Alvin Salim, Esti Yunitasari

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Background: Palliative care is caring holistically for patients and families to improve their quality of life. The approach by a multidisciplinary team requires integrated collaboration based on sufficient knowledge of the principles of palliative care as a whole, especially for nurses. Therefore, this study wants to find out the level of knowledge about palliative care of the nurses along the relationship with attitude and performance. Method: This study applies cross-sectional survey design and allows the respondents to fill two questionnaires to determine the level of knowledge and attitude toward palliative care, while one questionnaire is filled by the head nurse to evaluate nurses’ performance. The relationship was analyzed by Spearman rho’s correlation in alpha < 0.05 by SPSS. Results: The majority of respondents were females, age above 25 years old, and married. Most of the nurses are staff nurses and the ratio of education level is not significantly different. The knowledge level is poor, while the attitude and performance are in adequate level. Knowledge may affect attitude, but it does not happen toward performance. Conclusion: There is a need for increased knowledge about palliative care to improve attitude and work performance. Future researchers might use this finding as reference to conduct further study in improving knowledge of palliative care.

Keywords: Knowledge, attitude, work performance, palliative care.

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Authors: Mohammed Almohammedali, Peter Duncan, David Edgar

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The aim of this exploratory research is to understand further how organisations can evaluate their activities, which generate knowledge creation, to meet changing stakeholder expectations. A Scale of Knowledge (SoK) Framework is proposed which links knowledge management and organisational activities to changing stakeholder expectations. The framework was informed by the knowledge management literature, as well as empirical work conducted via a single case study of a multi-site hospital organisation in Saudi Arabia. Eight in-depth semi-structured interviews were conducted with managers from across the organisation regarding current and future stakeholder expectations, organisational strategy/activities and knowledge management. Data were analysed using thematic analysis and a hierarchical value map technique to identify activities that can produce further knowledge and consequently impact on how stakeholder expectations are met. The SoK Framework developed may be useful to practitioners as an analytical aid to determine if current organisational activities produce organisational knowledge which helps them meet (increasingly higher levels of) stakeholder expectations. The limitations of the research and avenues for future development of the proposed framework are discussed.

Keywords: Knowledge creation, knowledge management, organisational knowledge, scale of knowledge, knowledge impact.

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Authors: Khelood A. Mkalaf, Peter Gibson, John Flanagan

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This study investigates the relationship between the reliability of critical medical equipment (CME) and the effectiveness of CME maintenance management strategies in relation to patient outcomes in 84 public hospitals of a top 20 OECD country. The work has examined the effectiveness of CME maintenance management strategies used by the public hospital system of a large state run health organization. The conceptual framework was designed to examine the significance of the relationship between six variables: (1) types of maintenance management strategies, (2) maintenance services, (3) maintenance practice, (4) medical equipment reliability, (5) maintenance costs and (6) patient outcomes. The results provide interesting insights into the effectiveness of the maintenance strategies used. For example, there appears to be about a 1 in 10 000 probability of failure of anesthesia equipment, but these seem to be confined to specific maintenance situations. There are also some findings in relation to outsourcing of maintenance. For each of the variables listed, results are reported in relation to the various types of maintenance strategies and services. Decision-makers may use these results to evaluate more effective maintenance strategies for their CME and generate more effective patient outcomes.

Keywords: Critical medical equipment, maintenance strategy, patient outcomes, reliability.

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Authors: G. Sokhansefat, M. Delavar, M. Banedj-Schafii

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Recently research on human wayfinding has focused mainly on mental representations rather than processes of wayfinding. The objective of this paper is to demonstrate the rationality behind applying multi-agent simulation paradigm to the modeling of rescuer team wayfinding in order to develop computational theory of perceptual wayfinding in crisis situations using image schemata and affordances, which explains how people find a specific destination in an unfamiliar building such as a hospital. The hypothesis of this paper is that successful navigation is possible if the agents are able to make the correct decision through well-defined cues in critical cases, so the design of the building signage is evaluated through the multi-agent-based simulation. In addition, a special case of wayfinding in a building, finding one-s way through three hospitals, is used to demonstrate the model. Thereby, total rescue time for rescue operation during building fire is computed. This paper discuses the computed rescue time for various signage localization and provides experimental result for optimization of building signage design. Therefore the most appropriate signage design resulted in the shortest total rescue time in various situations.

Keywords: Multi-Agent system (MAS), Spatial Cognition, Wayfinding, Indoor Environment, Geospatial Information System (GIS).

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Authors: Daniella Kucsma

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The examination of the Public Service Organization’s performance evaluation includes several steps that help public organizations to develop a more efficient system. Public sector organizations have different characteristics than the competitive sector, so it can be stated that other/new elements become more important in their performance processes. The literature in this area is diverse, so highlighting an indicator system can be useful for introducing a system, but it is also worthwhile to measure the specific elements of the organization. In the case of a public service organization, due to the service obligation, it is usually possible to talk about a high number of users, so compliance is more difficult. For the organization, it is an important target to place great emphasis on the increase of service standards and the development of related processes. In this research, the health sector is given a prominent role, as it is a sensitive area where both organizational and individual performance is important for all participants. As a primary step, the content of the strategy is decisive, as this is important for the efficient structure of the process. When designing any system, it is important to review the expectations of the stakeholders, as this is primary when considering the design. The goal of this paper is to build the foundations of a performance management and indexing framework that can help a hospital to provide effective feedback and a direction that is important in assessing and developing a service and can become a management philosophy.

Keywords: health sector, public sector, performance management, strategy

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Authors: M. Ricardo Lang, A. Costa, I. Iesbik, K. Haag, L. Trindade Buffara, O. Reimann Junior, C. Auswaldt Steclan

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Stroke affects not only the individual, but has significant impacts on the social and family context. Therefore, it is necessary to know the peculiarities of each region, in order to contribute to regional public health policies effectively. Thus, the present study discusses biomarkers in a post-stroke population, admitted to a stroke unit (U-stroke) of reference in the southern region of Brazil. Biomarkers were analyzed, such as age, length of stay, mortality rate, survival time, risk factors and family history of stroke in patients after ischemic stroke. In this studied population, comparing men and women, it was identified that men were more affected than women, and the average age of women affected was higher, as they also had the highest mortality rate and the shortest hospital stay. The risk factors identified here were according to the global scenario; with systemic arterial hypertension (SAH) being the most frequent and those associated with sedentary lifestyle in women the most frequent (dyslipidemia, heart disease and obesity). In view of this, the importance of studies that characterize populations regionally is evident, strengthening the strategic planning of policies in favor of health care.

Keywords: Biomarkers, population, stroke, sex, stroke unit.

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Authors: Z. Karakus, Z. Ozer

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Nurses are responsible for the care and treatment of individuals, as well as health maintenance and education. Medication administration is an important part of health promotion. The administration of a medicine is a common but important clinical procedure for nurses because of its complex structure. Therefore, medication errors are inevitable for nurses or nursing students. Medication errors can cause ineffective treatment, patient’s prolonged hospital stay, disablement or death. Additionally, medication errors affect the global economy adversely by increasing health costs. Hence, preventing or decreasing of medication errors is a critical and essential issue in nursing. Nurse educators are in pursuit of new teaching methods to teach students significance of medication application. In the light of technological developments of this age, e-learning has started to be accepted as an important teaching method. E-learning is the use of electronic media and information and communication technologies in education. It has advantages such as flexibility of time and place, lower costs, faster delivery and lower environmental impact. Students can make their own schedule and decide the learning method. This study is conducted to determine the impact of e-learning on medication administration of nursing students.

Keywords: E-Learning, Medication Administration, Nursing, Nursing Students.

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Authors: Natasha Hussain, Maleeha Aslam, Robina Farooq

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Hepatitis B and hepatitis C are among the most significant hepatic infections all around the world that may lead to hepatocellular carcinoma. This study is first time performed at the blood transfussion centre of Omar hospital, Lahore. It aims to determine the sero-prevalence of these diseases by screening the apparently healthy blood donors who might be the carriers of HBV or HCV and pose a high risk in the transmission. It also aims the comparison between the sensitivity of two diagnostic tests; chromatographic immunoassay – one step test device and Enzyme Linked Immuno Sorbant Assay (ELISA). Blood serum of 855 apparently healthy blood donors was screened for Hepatitis B surface antigen (HBsAg) and for anti HCV antibodies. SPSS version 12.0 and X2 (Chi-square) test were used for statistical analysis. The seroprevalence of HCV was 8.07% by the device method and by ELISA 9.12% and that of HBV was 5.6% by the device and 6.43% by ELISA. The unavailability of vaccination against HCV makes it more prevalent. Comparing the two diagnostic methods, ELISA proved to be more sensitive.

Keywords: ELISA, Sensitivity comparison of diagnostic tests, seroprevalence of Hepatitis B and C

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Authors: Laila Seada, Nouf Al Gharbi, Shaimaa Dawa

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Although skin cancers are prevalent worldwide, it is uncommon in Ha’il region in the Kingdom of Saudi Arabia, mostly non-melanoma sub-type. During a 4-year period from 2014 to 2017, out of a total of 120 cases of skin lesions, 29 non-melanoma cancers were retrieved from histopathology files obtained from King Khalid Hospital. As part of the study, all cases of skin cancer diagnosed during 2014 -2017 have been revised and the clinicopathological data recorded. The results show that Basal cell carcinoma (BCC) was the most common neoplasm (36%), followed by cutaneous lymphomas (mostly mycosis fungoides 25%), squamous cell carcinoma (SCC) (21%) and dermatofibrosarcoma protuberans (DFSP) (11%). Only one case of metastatic carcinoma was recorded. BCC nodular type was the most prevalent, with a mean age 57.6 years and mean size 2.73 cm. SCC was mostly grade 2, with mean size 1.9 cm and an older mean age of 72.3 cm. Increased size of lesion positively correlated with older age (p = 0.001). Non-melanoma skin cancer in Ha’il region is not frequently encountered. BCC is the most frequent followed by cutaneous T-cell lymphomas and SCC. The findings in this study were in accordance with other parts of, but much lower than other parts of the world.

Keywords: Non melanoma skin cancer, Hail Region, histopathology, BCC.

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Authors: Kevin Fong-Rey Liu, Ken Yeh, Cheng-Wu Chen, Han-Hsi Liang

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The sanitary sewerage connection rate becomes an important indicator of advanced cities. Following the construction of sanitary sewerages, the maintenance and management systems are required for keeping pipelines and facilities functioning well. These maintenance tasks often require sewer workers to enter the manholes and the pipelines, which are confined spaces short of natural ventilation and full of hazardous substances. Working in sewers could be easily exposed to a risk of adverse health effects. This paper proposes the use of Bayesian belief networks (BBN) as a higher level of noncarcinogenic health risk assessment of sewer workers. On the basis of the epidemiological studies, the actual hospital attendance records and expert experiences, the BBN is capable of capturing the probabilistic relationships between the hazardous substances in sewers and their adverse health effects, and accordingly inferring the morbidity and mortality of the adverse health effects. The provision of the morbidity and mortality rates of the related diseases is more informative and can alleviate the drawbacks of conventional methods.

Keywords: Bayesian belief networks, sanitary sewerage, healthrisk assessment, hazard quotient, target organ-specific hazard index.

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Authors: Simon B. N. Thompson

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Cortisol is essential to the regulation of the immune system and yawning is a pathological symptom of multiple sclerosis (MS). Electromyography activity (EMG) in the jaw muscles typically rises when the muscles are moved and with yawning is highly correlated with cortisol levels in healthy people. Saliva samples from 59 participants were collected at the start and after yawning, or at the end of the presentation of yawning-provoking stimuli, in the absence of a yawn, together with EMG data and questionnaire data: Hospital Anxiety and Depression Scale, Yawning Susceptibility Scale, General Health Questionnaire, demographic, health details. Exclusion criteria: chronic fatigue, diabetes, fibromyalgia, heart condition, high blood pressure, hormone replacement therapy, multiple sclerosis, stroke. Significant differences were found between the saliva cortisol samples for the yawners, t (23) = -4.263, p = 0.000, as compared with the non-yawners between rest and post-stimuli, which was nonsignificant. Significant evidence was found to support the Thompson Cortisol Hypothesis suggesting that rises in cortisol levels are associated with yawning. Further research is exploring the use of cortisol as an early diagnostic tool for MS. Ethics approval granted and professional code of conduct, confidentiality, and safety issues are approved therein.

Keywords: Cortisol, Multiple Sclerosis, Yawning, Thompson’s Cortisol Hypothesis.

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Authors: Anthony Bawa, Konstantinos Banitsas

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Rheumatism is a muscular disorder that affects the muscles of the upper and lower limbs. This condition could potentially progress to impair the movement of patients. This study aims to investigate the hip muscular imbalance in patients with chronic rheumatism. A clinical trial involving a total of 15 participants, made up of 10 patients and five control subjects, took place in KATH Hospital between August and September. Participants recruited for the study were of age 54 ± 8 years, weight 65 ± 8 kg, and height 176 ± 8 cm. Muscle signals were recorded from the rectus femoris, and vastus lateralis on the right and left hip of participants. The parameters used in determining the hip muscular imbalances were the maximum voluntary contraction (MVC%), the mean difference, and hip muscle fatigue levels. The mean signals were compared using a t-test, and the metrics for muscle fatigue assessment were based on the root mean square (RMS), mean absolute value (MAV) and mean frequency (MEF), which were computed between the hip muscles of participants. The results indicated that there were significant imbalances in the muscle coactivity between the right and left hip muscles of patients. The patients’ MVC values were observed to be above 10% when compared with control subjects. Furthermore, the mean difference was seen to be higher with p > 0.002 among patients, which indicated clear differences in the hip muscle contraction activities. The findings indicate significant hip muscular imbalances for patients with rheumatism compared with control subjects. Information about the imbalances among patients will be useful for clinicians in designing therapeutic muscle-strengthening exercises.

Keywords: Muscular, imbalances, rheumatism, hip.

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Authors: Kjersti Engan, Thor Ole Gulsrud, Karl Fredrik Fretheim, Barbro Furebotten Iversen, Liv Eriksen

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Clusters of microcalcifications in mammograms are an important sign of breast cancer. This paper presents a complete Computer Aided Detection (CAD) scheme for automatic detection of clustered microcalcifications in digital mammograms. The proposed system, MammoScan μCaD, consists of three main steps. Firstly all potential microcalcifications are detected using a a method for feature extraction, VarMet, and adaptive thresholding. This will also give a number of false detections. The goal of the second step, Classifier level 1, is to remove everything but microcalcifications. The last step, Classifier level 2, uses learned dictionaries and sparse representations as a texture classification technique to distinguish single, benign microcalcifications from clustered microcalcifications, in addition to remove some remaining false detections. The system is trained and tested on true digital data from Stavanger University Hospital, and the results are evaluated by radiologists. The overall results are promising, with a sensitivity > 90 % and a low false detection rate (approx 1 unwanted pr. image, or 0.3 false pr. image).

Keywords: mammogram, microcalcifications, detection, CAD, MammoScan μCaD, VarMet, dictionary learning, texture, FTCM, classification, adaptive thresholding

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Authors: Jacqueline R. T. Alipo-on, Francesca I. F. Escobar, Myles J. T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases which are considered as one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis on the ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heart beat types. The dataset used in this work is the synthetic MIT-Beth Israel Hospital (MIT-BIH) Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: Heartbeat classification, convolutional neural network, electrocardiogram signals, ECG signals, generative adversarial networks, long short-term memory, LSTM, ResNet-50.

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Authors: V. Thulasi Bai, Srivatsa S. K.

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Deaths from cardiovascular diseases have decreased substantially over the past two decades, largely as a result of advances in acute care and cardiac surgery. These developments have produced a growing population of patients who have survived a myocardial infarction. These patients need to be continuously monitored so that the initiation of treatment can be given within the crucial golden hour. The available conventional methods of monitoring mostly perform offline analysis and restrict the mobility of these patients within a hospital or room. Hence the aim of this paper is to design a Portable Cardiac Telemedicine System to aid the patients to regain their independence and return to an active work schedule, there by improving the psychological well being. The portable telemedicine system consists of a Wearable ECG Transmitter (WET) and a slightly modified mobile phone, which has an inbuilt ECG analyzer. The WET is placed on the body of the patient that continuously acquires the ECG signals from the high-risk cardiac patients who can move around anywhere. This WET transmits the ECG to the patient-s Bluetooth enabled mobile phone using blue tooth technology. The ECG analyzer inbuilt in the mobile phone continuously analyzes the heartbeats derived from the received ECG signals. In case of any panic condition, the mobile phone alerts the patients care taker by an SMS and initiates the transmission of a sample ECG signal to the doctor, via the mobile network.

Keywords: WET, ECG analyzer, Bluetooth, mobilecellular network, high risk cardiac patients.

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Authors: Laila Seada, Hanan Oreiby, Fawaz Al Rashid, Ashraf Negm

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Background and Objective: In most areas of the world, the incidence of thyroid cancer has been increasing over the last decade, mostly due to a combination of early detection of the neoplasm resulting from sensitive procedures and increased population exposure to radiation and unrecognized carcinogens. Methods: Cases of thyroid cancer have been retrieved from the cancer registry at King Khalid Hospital during the period from August 2012 to April 2016. Age, gender and histopathologic types have been recorded. Results: Thyroid carcinoma ranked as the second most common malignancy in females (25%) after breast cancer (31%). It constituted 20.8% of all newly diagnosed cancer cases. As for males, it ranked the 4^th type of malignancy after gastrointestinal cancer, lymphomas and soft tissue sarcomas. Mean age for females and males was 38.7 +/- 13.2 and 60.25 +/- 11.5 years, respectively, and the difference between the two groups was statistically significant (p value = 0.0001). Fifty-five (82%) were papillary carcinomas including 10 follicular variant of papillary (FVPC), and eight papillary micro carcinomas (PMC) and two tall cell/oncocytic variants. Follicular carcinomas constituted two (3.1%), while two (3.1%) were anaplastic, and two (3.1%) were medullary. Conclusion: Thyroid cancer incidence in Hail is ranking as the 2^nd most common female malignancy similar to other regions in the Kingdom. However, this high incidence contrasts with much lower rates worldwide.

Keywords: Thyroid, Hail, papillary, micro carcinoma.

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Authors: Youngsub Oh, Youngsoon Kim

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As the second largest group among international marriages in Korea, Vietnamese married immigrant women have been exposed to psychological crisis like divorce and family violence. The purpose of this study is to understand how to counsel those women from the perspective of indigenous healing as their own psychological problem-solving way. To this end, this study reviewed Vietnamese cultural literatures on their mentality as well as Vietnamese medical literatures on indigenous healing. The research results are as follows: First, cultural foundations that have formed Vietnamese mentality are Confucian value system, reserved communication, and religious pluralism. These cultural backgrounds play an important role in understanding their own therapeutic tradition. Second, Vietnamese indigenous healing considers cause of mental disease as a collapse of balance between mind and body and environment. Thus, indigenous treatment deals with psychological problems through a recovery of the balance from the holistic perspective. In fact, indigenous healing has been actively practiced in everyday place as well as hospital until today. The implications of Vietnamese indigenous healing for multicultural counseling in Korea are as follows: First, Korean counselors need to interactively understand their own assumptions on indigenous healing as well as counselees’ own assumptions. Second, a variety of psychological intervention strategies can be drawn from Vietnamese indigenous healing. Third, indigenous healing needs to be integrated with modern techniques of counseling and psychotherapy, as both treatments are not mutually exclusive but complementary.

Keywords: Indigenous healing, Vietnamese married immigrant women in Korea, multicultural counseling.

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Authors: Juliana Panova

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Severe symptoms, such as dissociation, depersonalization, self-mutilation, suicidal ideations and gestures, are the main reasons for a person to be diagnosed with Borderline Personality Disorder (BPD) and admitted to an inpatient Psychiatric Hospital. However, these symptoms are also indicators of a severe traumatic history as indicated by the extensive research on the topic. Unfortunately patients with such clinical presentation often are treated repeatedly only for their symptomatic behavior, while the main cause for their suffering, the trauma itself, is usually left unaddressed therapeutically. All of the highly structured, replicable, and manualized treatments lack the recognition of the uniqueness of the person and fail to respect his/her rights to experience and react in an idiosyncratic manner. Thus the communicative and adaptive meaning of such symptomatic behavior is missed. Only its pathological side is recognized and subjected to correction and stigmatization, and the message that the person is damaged goods that needs fixing is conveyed once again. However, this time the message would be even more convincing for the victim, because it is sent by mental health providers, who have the credibility to make such a judgment. The result is a revolving door of very expensive hospitalizations for only a temporary and patchy fix. In this way the patients, once victims of abuse and hardship are left invalidated and thus their re-victimization is perpetuated in their search for understanding and help. Keywordsborderline personality disorder (BPD), complex PTSD, integrative treatment of trauma, re-victimization of trauma victims.

Keywords: borderline personality disorder (BPD), complex PTSD, integrative treatment of trauma, re-victimization of trauma victims.

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Authors: R. Litt, A. Brown

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Aims: We aimed to assess the efficiency of ‘Attend Anywhere’ orthodontic clinics within a district general hospital during COVID- 19. Our secondary aim was to pilot a questionnaire to assess patient satisfaction with virtual orthodontic appointments. Design: The study design is a service evaluation including pilot questionnaire. Methods: The average number of patients seen per virtual clinic and the number of patients failing to attend was compared to face-to-face clinics. The capability of virtual appointments to be successful in preventing the need for a face-to-face appointment was assessed. Patients were invited to complete a telephone pilot questionnaire focusing on patient satisfaction and accessibility. Results: There was a small increase in the number of patients failing to attend virtual appointments, with a third of the patients who did not attend failing to receive the appointment link. 81.9% of virtual clinic appointments were successful and prevented the need for a face-to-face appointment. Overall patients were very satisfied with their virtual orthodontic appointment and the majority required no assistance to access the service. Conclusions: The use of ‘Attend Anywhere’ clinics in orthodontics offers patients and clinicians an effective and efficient alternative to face-to-face appointments that patients on average find easy to use and completely satisfactory.

Keywords: Clinics, COVID-19, orthodontics, patient satisfaction, virtual.

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Authors: W. Y. Wan Fairos, W. H. Wan Azaki, L. Mohamad Alias, Y. Bee Wah

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Dengue fever has become a major concern for health authorities all over the world particularly in the tropical countries. These countries, in particular are experiencing the most worrying outbreak of dengue fever (DF) and dengue haemorrhagic fever (DHF). The DF and DHF epidemics, thus, have become the main causes of hospital admissions and deaths in Malaysia. This paper, therefore, attempts to examine the environmental factors that may influence the recent dengue outbreak. The aim of this study is twofold, firstly is to establish a statistical model to describe the relationship between the number of dengue cases and a range of explanatory variables and secondly, to identify the lag operator for explanatory variables which affect the dengue incidence the most. The explanatory variables involved include the level of cloud cover, percentage of relative humidity, amount of rainfall, maximum temperature, minimum temperature and wind speed. The Poisson and Negative Binomial regression analyses were used in this study. The results of the analyses on the 915 observations (daily data taken from July 2006 to Dec 2008), reveal that the climatic factors comprising of daily temperature and wind speed were found to significantly influence the incidence of dengue fever after 2 and 3 weeks of their occurrences. The effect of humidity, on the other hand, appears to be significant only after 2 weeks.

Keywords: Dengue Fever, Dengue Hemorrhagic Fever, Negative Binomial Regression model, Poisson Regression model.

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Authors: Paria Soleimani, Arezoo Neshati

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Myocardial infarction is one of the leading causes of death in the world. Some of these deaths occur even before the patient reaches the hospital. Myocardial infarction occurs as a result of impaired blood supply. Because the most of these deaths are due to coronary artery disease, hence the awareness of the warning signs of a heart attack is essential. Some heart attacks are sudden and intense, but most of them start slowly, with mild pain or discomfort, then early detection and successful treatment of these symptoms is vital to save them. Therefore, importance and usefulness of a system designing to assist physicians in early diagnosis of the acute heart attacks is obvious. The main purpose of this study would be to enable patients to become better informed about their condition and to encourage them to seek professional care at an earlier stage in the appropriate situations. For this purpose, the data were collected on 711 heart patients in Iran hospitals. 28 attributes of clinical factors can be reported by patients; were studied. Three logistic regression models were made on the basis of the 28 features to predict the risk of heart attacks. The best logistic regression model in terms of performance had a C-index of 0.955 and with an accuracy of 94.9%. The variables, severe chest pain, back pain, cold sweats, shortness of breath, nausea and vomiting, were selected as the main features.

Keywords: Coronary heart disease, acute heart attacks, prediction, logistic regression.

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Authors: Marjan Mahdavi-Roshan, Arsalan Salari, Mahboobeh Gholipour, Moona Naghshbandi

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Background and objectives: Before any nutritional intervention, it is necessary to have the prospect of eating habits of people with cardiovascular risk factors. In this study, we assessed the adherence of healthy diet based on Mediterranean dietary pattern and related factors in adults in the north of Iran. Methods: This study was conducted on 550 men and women with cardiovascular risk factors that referred to Heshmat hospital in Rasht, northern Iran. Information was collected by interview and reading medical history and measuring anthropometric indexes. The Mediterranean Diet Adherence Screener was used for assessing dietary adherence, this screener was modified according to religious beliefs and culture of Iran. Results: The mean age of participants was 58±0.38 years. The mean of body mass index was 27±0.01 kg/m², and the mean of waist circumference was 98±0.2 cm. The mean of dietary adherence was 5.76±0.07. 45% of participants had low adherence, and just 4% had suitable adherence. The mean of dietary adherence in men was significantly higher than women (p=0. 07). Participants in rural area and high educational participants insignificantly had an unsuitable dietary Adherence. There was no significant association between some cardiovascular disease risk factors and dietary adherence. Conclusion: Education to different group about dietary intake correction and using a Mediterranean dietary pattern that is similar to dietary intake in the north of Iran, for controlling cardiovascular disease is necessary.

Keywords: Dietary adherence, Mediterranean dietary pattern, cardiovascular disease, north of Iran.

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Authors: Farhan Ismaeel Dakheel, Raoof Smko, K. Negrat, Abdelsalam Almarimi

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In this paper we used data mining techniques to identify outlier patients who are using large amount of drugs over a long period of time. Any healthcare or health insurance system should deal with the quantities of drugs utilized by chronic diseases patients. In Kingdom of Bahrain, about 20% of health budget is spent on medications. For the managers of healthcare systems, there is no enough information about the ways of drug utilization by chronic diseases patients, is there any misuse or is there outliers patients. In this work, which has been done in cooperation with information department in the Bahrain Defence Force hospital; we select the data for Cardiac patients in the period starting from 1/1/2008 to December 31/12/2008 to be the data for the model in this paper. We used three techniques for finding the drug utilization for cardiac patients. First we applied a clustering technique, followed by measuring of clustering validity, and finally we applied a decision tree as classification algorithm. The clustering results is divided into three clusters according to the drug utilization, for 1603 patients, who received 15,806 prescriptions during this period can be partitioned into three groups, where 23 patients (2.59%) who received 1316 prescriptions (8.32%) are classified to be outliers. The classification algorithm shows that the use of average drug utilization and the age, and the gender of the patient can be considered to be the main predictive factors in the induced model.

Keywords: Data Mining, Clustering, Classification, Drug Utilization..

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

Abstract:

Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: Breast cancer, health diagnosis, Machine Learning, biomarker classification, Neural Network.

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Authors: Simon B. N. Thompson

Abstract:

Cortisol is important to our immune system, regulates our stress response, and is a factor in maintaining brain temperature. Saliva cortisol is a practical and useful non-invasive measurement that signifies the presence of the important hormone. Electrical activity in the jaw muscles typically rises when the muscles are moved during yawning and the electrical level is found to be correlated with the cortisol level. In two studies using identical paradigms, a total of 108 healthy subjects were exposed to yawning-provoking stimuli so that their cortisol levels and electrical nerve impulses from their jaw muscles was recorded. Electrical activity is highly correlated with cortisol levels in healthy people. The Hospital Anxiety and Depression Scale, Yawning Susceptibility Scale, General Health Questionnaire, demographic, health details were collected and exclusion criteria applied for voluntary recruitment: chronic fatigue, diabetes, fibromyalgia, heart condition, high blood pressure, hormone replacement therapy, multiple sclerosis, and stroke. Significant differences were found between the saliva cortisol samples for the yawners as compared with the non-yawners between rest and post-stimuli. Significant evidence supports the Thompson Cortisol Hypothesis that suggests rises in cortisol levels are associated with yawning. Ethics approval granted and professional code of conduct, confidentiality, and safety issues are approved therein.

Keywords: Cortisol, Diagnosis, Neurological Disease, Thompson Cortisol Hypothesis, Yawning.

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Authors: Carmen Grigoraş, Victor Grigoraş, Daniela Boişteanu

Abstract:

The standard investigational method for obstructive sleep apnea syndrome (OSAS) diagnosis is polysomnography (PSG), which consists of a simultaneous, usually overnight recording of multiple electro-physiological signals related to sleep and wakefulness. This is an expensive, encumbering and not a readily repeated protocol, and therefore there is need for simpler and easily implemented screening and detection techniques. Identification of apnea/hypopnea events in the screening recordings is the key factor for the diagnosis of OSAS. The analysis of a solely single-lead electrocardiographic (ECG) signal for OSAS diagnosis, which may be done with portable devices, at patient-s home, is the challenge of the last years. A novel artificial neural network (ANN) based approach for feature extraction and automatic identification of respiratory events in ECG signals is presented in this paper. A nonlinear principal component analysis (NLPCA) method was considered for feature extraction and support vector machine for classification/recognition. An alternative representation of the respiratory events by means of Kohonen type neural network is discussed. Our prospective study was based on OSAS patients of the Clinical Hospital of Pneumology from Iaşi, Romania, males and females, as well as on non-OSAS investigated human subjects. Our computed analysis includes a learning phase based on cross signal PSG annotation.

Keywords: Artificial neural networks, feature extraction, obstructive sleep apnea syndrome, pattern recognition, signalprocessing.

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Authors: Ravi Kiran Pothamsetty, Radha Rani Ghosh, Baby Paul Thaliath

Abstract:

Radiation therapy has undergone many advancements and evloved from 2D to 3D. Recently, with rapid pace of drug discoveries, cutting edge technology, and clinical trials has made innovative advancements in computer technology and treatment planning and upgraded to intensity modulated radiotherapy (IMRT) which delivers in homogenous dose to tumor and normal tissues. The present study was a hospital-based experience comparing two different conformal radiotherapy techniques for brain tumors. This analytical study design has been conducted at Regional Cancer Centre, India from January 2014 to January 2015. Ten patients have been selected after inclusion and exclusion criteria. All the patients were treated on Artiste Siemens Linac Accelerator. The tolerance level for maximum dose was 6.0 Gyfor lenses and 54.0 Gy for brain stem, optic chiasm and optical nerves as per RTOG criteria. Mean and standard deviation values of PTV98%, PTV 95% and PTV 2% in IMRT were 93.16±2.9, 95.01±3.4 and 103.1±1.1 respectively; for 3DCRT were 91.4±4.7, 94.17±2.6 and 102.7±0.39 respectively. PTV max dose (%) in IMRT and 3D-CRT were 104.7±0.96 and 103.9±1.0 respectively. Maximum dose to the tumor can be delivered with IMRT with acceptable toxicity limits. Variables such as expertise, location of tumor, patient condition, and TPS influence the outcome of the treatment.

Keywords: IMRT, 3D CRT, Brain, tumors, OARs, RTOG.

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Authors: Nadir A. Carreón, Christa Sonderer, Aakarsh Rao, Roman Lysecky

Abstract:

With the advent of complex software and increased connectivity, security of life-critical medical devices is becoming an increasing concern, particularly with their direct impact to human safety. Security is essential, but it is impossible to develop completely secure and impenetrable systems at design time. Therefore, it is important to assess the potential impact on security and safety of exploiting a vulnerability in such critical medical systems. The common vulnerability scoring system (CVSS) calculates the severity of exploitable vulnerabilities. However, for medical devices, it does not consider the unique challenges of impacts to human health and privacy. Thus, the scoring of a medical device on which a human life depends (e.g., pacemakers, insulin pumps) can score very low, while a system on which a human life does not depend (e.g., hospital archiving systems) might score very high. In this paper, we present a Medical Vulnerability Scoring System (MVSS) that extends CVSS to address the health and privacy concerns of medical devices. We propose incorporating two new parameters, namely health impact and sensitivity impact. Sensitivity refers to the type of information that can be stolen from the device, and health represents the impact to the safety of the patient if the vulnerability is exploited (e.g., potential harm, life threatening). We evaluate 15 different known vulnerabilities in medical devices and compare MVSS against two state-of-the-art medical device-oriented vulnerability scoring system and the foundational CVSS.

Keywords: Common vulnerability system, medical devices, medical device security, vulnerabilities.

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