• Tab-Net Powered Assessment for Early Recognition of Neurodevelopmental Disorders in Children Below Three Years using Symptom Analytics 

  Chamoda, B.P.; Vasanthapriyan, S.; Dampalessa, D. R. C. G. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Neurons are the basic building blocks of the human brain and nervous system. In the past few years, Neurodevelopmental Disorders (NDD) in toddlers has been increasing in the world year by year and this is becoming a major ...
• Detecting scam job advertisement using machine learning techniques 

  Natha, M.S.S.; Amath A.A.S., A.A.S.; Erandi, J.D.T. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Automated detection of scam job advertisements is critical for ensuring safer online recruitment. This study proposes a machine learning–based approach for detecting fraudulent job postings using textual and metadata ...
• Predictive modeling for injury risk and performance analysis in collegiate and female basketball players 

  Dilakshigan, A.; Erandi, J.D.T; Chandana, A.W.S. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  This paper examines a machine-learning model of injury prediction and performance assessment on female and collegiate-level basketball players through interpretable workload-based models. The dataset was gathered among ...
• Data-driven prediction of university admission cutoff marks in Sri Lanka using machine learning 

  Theeksha, J.R.N.; Kudagamage, U.P. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Admissions into universities in Sri Lanka are determined through the cutoff marks published annually in the University Grants Commission (UGC), although the procedure itself is not only unclear but opaque to students as ...
• AI-powered predictive modeling and comparative machine learning analysis for improving hospital operational efficiency 

  Rathnaweera, R.C.L.U.; Somaweera, W.T.S.; Sandaruwan, R.M.T. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  The study addresses the critical problem that Sri Lankan state-run hospitals have no data-driven predictive tools of patient movement and resource allocation that have led to longer patients waiting and poor bed utilization. ...

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