Browsing by Author "Wickramasinghe, B.M.G.S.T.S.K."

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Open Access
A Data-Driven Approach to Predicting Ischemic Heart Disease Risk in Monaragala: Integrating Lifestyle and Symptom Factors with Machine Learning
(Faculty of Engineering, 2025-09-09) Meddepola, M.A.R.L.; Wickramasinghe, B.M.G.S.T.S.K.
Ischemic Heart Disease (IHD) remains a leading cause of mortality worldwide and presents a critical challenge in underserved rural areas such as Monaragala, Sri Lanka. Traditional IHD prediction methods predominantly depend on clinical diagnostics like ECGs and blood tests, which are often unavailable or inaccessible in such regions. This study aims to bridge this gap by developing a machine learning-based prediction model that utilizes only lifestyle and symptom-related data, eliminating the need for invasive clinical procedures. A dataset comprising lifestyle habits (e.g., diet, smoking, alcohol use, exercise) and symptom indicators (e.g., chest pain, fatigue, dizziness) was collected via surveys. Feature selection using Logistic Regression identified the top eight most relevant predictors. Five machine learning algorithms, Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Decision Tree, and Random Forest, were trained and evaluated. Among them, the Random Forest model achieved the highest performance with an accuracy of 83.5%, precision of 0.86, recall of 0.78, and F1- score of 0.81, demonstrating strong predictive capability based solely on non-clinical features. In addition, a web-based self-assessment tool was developed to make the model accessible to the public, particularly targeting individuals in rural areas with limited healthcare access. The tool enables users to input basic lifestyle and symptom information and receive a real-time risk assessment. The findings confirm that the model leveraging lifestyle and symptom data can effectively identify individuals at risk of IHD. This approach supports the development of scalable, low-cost, and user-friendly screening tools that can enhance early detection and preventive care, especially in rural and resource-constrained settings.
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Exploring Sri Lankan Sign Language (Slsl) and Its Role in Bridging Communication Barriers: A Review of Translation Tools and Techniques
(SLIIT, Faculty of Engineering, 2024-10) Wickramasinghe, B.M.G.S.T.S.K.; Punchimudiyanse, M.
Deaf-mute persons frequently struggle to communicate their views to the speaking population in society since their major form of communication is Sri Lankan Sign Language (SLSL). This occurs in schools, government buildings, marketplaces, the availability of medical services, and when people's socioeconomic demands are met. As of the first quarter of 2020, the number of deaf people in Sri Lanka who use sign language is estimated to be 107,000, or around 0.4% of the country's total population and 1.2% of the labour force overall. The majority of issues are caused by the lack of SLSL interpreters and expertise or the scarcity of digital translation tools in SLSL. The National Institute of Education Sri Lanka (NIESL) publishes a variety of books that are utilized in deaf schools all around the island to address these kinds of issues. Additionally, the Sri Lanka Central Federation for Deaf (SLCFD) has helped with the publication of sign books. However, there are still several problems that cause the underutilization of the deaf population as a productive workforce, due to lack of SLSL vocabulary and public ignorance. Deaf-mute communication has been the subject of several studies and prototype implementations over the last three to four decades all over the world. Additionally, recent developments in parallel processing have allowed researchers to enhance these deaf-mute solutions. However, the majority of SLSL research focuses on language issues, with a few studies in the technological field. A significant reason for the decreased contribution to this field of study is the complexity of SLSL. A two-way conversation between a hearing person and a deaf person is necessary for typical communication between the two groups of people. The communication between deaf and hearing people is the topic of this study. SLSL's conversational approach often uses a Sign for each Tamil or Sinhala word or sentence. A single posture, multiple postures, and multiple postures with a movement sequence are the foundations for SLSL indications.