Research Publications Authored by SLIIT Staff
Permanent URI for this communityhttps://rda.sliit.lk/handle/123456789/4195
This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.
Browse
2 results
Search Results
Publication Embargo Health Care – A Personalized Guidance for Non-Communicable Diseases(IEEE, 2022-12-09) Dakshima, D.D.T.D; Seliya Mindula, K; Rathnayake, R.M.S.J; Kasthuriarachchi, S; Buddhi Chathuranga, A.K; Lunugalage, DAll people expect to live a healthy life. But today about eighty million people a year suffer from non-communicable diseases. Among non-communicable diseases, heart disease and diabetes are at the forefront, and the number of deaths due to heart disease is rising in people with diabetes. Changes in lifestyle, work-related stress and bad food habits, and smoking addiction contribute to the increase in the rate of several heart diseases and diabetes diseases. Therefore, a reliable and accurate system is needed to identify such diseases in time for proper treatment. The methodology proposed in this research is based on Machine learning classification techniques using Random Forest (RF), Logistic Regression, Gradient Boosting, etc. It is an android mobile application. The prognosis process gives a cardiac risk analysis percentage based on the patient’s heart condition and a diabetic risk analysis percentage based on the diabetic condition by the Kaggle dataset. Accordingly, a system was proposed with daily guidelines including calculation of risk level, Exercise recommendation, Meal planner, and stress-releaser. The accuracy of the proposed system was risk calculation of heart at 82,75%, risk calculation of Diabetics at 81.66%, Meal planner at 89.8%, the exercise scheduler Cardiac status prediction at 73.57%, diabetic status prediction at 78.57%, body performance prediction 74.68% and stress release 100%. This system helps to prevent the associated risk levels and keep healthy life.Publication Embargo Healthy Heart – Heart Risk Prediction System on Personalized Guidance for Heart Patients(IEEE, 2022-07-18) Bandara, K.R.C; Dureksha, D.D.T.D; Pinidiya, S.C; Amarasinghe, R.M.G.H; Thelijjagoda, S; Kishara, JHuman heart is the principal part of the human body. Change in human lifestyle, work related stress and unhealthy food habits contribute to the increase in rate of numerous heart related diseases. In accordance with several research, various heart diseases have been the key reason for deaths in Sri Lanka. According to the 2018 records, stroke affected 31%, coronary heart disease affected 23%, and ischemic heart disease affected 14%. Therefore, there is a need for an automated system which will enhance medical efficiency and to identify such diseases in time for proper treatment. The proposed system takes physical and medical datasets of heart patients as manual input parameters and predicts the patient’s risk of having a heart disease. Prediction process grants the patient a risk level according to the heart condition and proposes a personalized daily guidance for the patient to avoid risks associated with, along with a meal planner, exercise scheduler and a stress releaser as well as alert the patient well in advance. The system will present an efficient technique of predicting heart diseases using machine learning approaches to analyze huge complex medical data. Some of the used algorithms are Random Forest, Logistic regression, Decision tree classifier etc... The research mainly aims to prevent the escalation of heart diseases in patients and lead them to a healthy lifestyle.