https://ir.kdu.ac.lk/handle/345/8353 2026-04-06T12:55:12Z https://ir.kdu.ac.lk/handle/345/8788 A Comprehensive Review of Automated ICD-10 Categorization Model: Methodologies, Challenges, and Future Directions Chinthika, AHS; Dissanayake, DMKS; Kaumal, WMS; Madhubashitha, WNNA; Sandamali, ERC In healthcare systems worldwide, the manual assignment of ICD-10 (International Classification of Diseases, 10th Revision) codes presents significant challenges, including resource constraints, lengthy processing times, and potential inaccuracies. This comprehensive review of the literature summarizes and analyzes existing research on automated ICD-10 coding systems, focusing on machine learning methodologies such as decision trees, natural language processing (NLP), and deep learning models. The review comprehensively evaluates the performance, accuracy, and implementation challenges of these techniques across diverse healthcare settings. By examining studies from multiple healthcare settings, this paper highlights the potential of automated systems to improve diagnostic precision, reduce manual workloads, and enhance overall healthcare efficiency. The evaluation highlights major obstacles, including data availability, integration with existing systems, and the need for ongoing training of healthcare professionals, with brief implications for developing countries like Sri Lanka. Finally, this comprehensive analysis recommends future research areas to help automated ICD-10 coding systems become more widely used, which would ultimately lead to better healthcare outcomes worldwide. 2024-01-01T00:00:00Z https://ir.kdu.ac.lk/handle/345/8787 Enhance Tea Quality and Market Stability with Advanced Technology: A Strategic Management Approach Gunawardhana, RKKG; Kathriarachchi, RPS The tea sector has a substantial impact on the world economy; however, it faces difficulties such as unstable markets, uneven tea leaf quality, and ineffective inventory management. Therefore, to improve tea quality and market stability, this study suggests a web-based application that combines cutting-edge technology, such as image processing, vehicle monitoring, and predictive analytics. The main goal was to create a complete solution that enhanced the ability of tea producers and processors to make decisions and operate more efficiently. The methodology of the study involved designing a system with five key components: predictive analytics for market forecasting, vehicle monitoring for logistics optimization, message control for stakeholder communication, tea leaf quality assessment through advanced image processing, and tea type management for inventory control. This integrated approach streamlines the operations in tea manufacturing, and it provides valuable insights into market trends and consumer preferences. The findings of the study indicate that the implementation of this system leads to improved tea quality, enhanced transportation efficiency, and better market responsiveness. However, challenges such as technology adoption and data integration remain. Future research will focus on refining these technologies and exploring their scalability across the industry. improves the competitiveness and sustainability of the tea sector by presenting a strategic framework that makes use of state-of-the-art technologies expenses. These difficulties include unstable markets, uneven tea leaf quality, and ineffective inventory management. Particularly small and medium-sized tea factories deal with a number of challenges in managing supply chains, upholding product quality, and embracing technological improvements. In addition, the tea business is vulnerable to changes in consumer tastes and price volatility in the market. Tea companies may experience lower profitability and a loss of market share if they are unable to predict market trends with sufficient accuracy and adjust to changing consumer preferences. In order to address critical issues. 2024-01-01T00:00:00Z https://ir.kdu.ac.lk/handle/345/8786 Identification and Assessment of Key Performance Indicators in Sri Lankan Volleyball Peiris, HMDR; Pradeep, RMM Player performance analysis and game strategy classification have seen significant advancements in global volleyball. However, these developments have been largely absent in Sri Lanka's volleyball landscape, where minimal research has been conducted. This study addresses the need to identify and evaluate key performance indicators (KPIs) specific to Sri Lankan volleyball. As an initial step, 25 research papers were reviewed, resulting in a preliminary list of 13 KPIs. To calibrate these KPIs, 10 interviews were conducted with coaches and volleyball experts, leading to the addition of 5 more KPIs. In the final phase, a questionnaire survey was administered to volleyball coaches and experts to evaluate and prioritize the KPIs. All 10 responses from the questionnaire were evaluated through a weighted scoring system, considering factors such as experience level, type of players trained, and coaching level. This process culminated in a final list of 12 KPIs: Flexibility, Aerobic Endurance, Hand Strength to Body Weight, Agility, Explosive Power (Lower Body), Explosive Power (Upper Body), Speed, Height, Weight, Age, Body Composition, and Skills and Game Conditions. This comprehensive approach ensures that the identified KPIs are both relevant and tailored to the local context, providing a solid foundation for future performance evaluation models in Sri Lankan volleyball. 2024-01-01T00:00:00Z https://ir.kdu.ac.lk/handle/345/8785 Exploration of Technological Interventions for Borderline Personality Disorder Jayasundera, SABN; Ilmini, WMKS; De Silva, MKOK Borderline personality disorder (BPD) is a complex, challenging, and prevalent mental health condition causing significant distress to those who are suffering. Due to the subtle complexities and overlapping symptoms associated with BPD, early diagnosis can be challenging, often leading to a less favourable prognosis. To explore the technologicalbased interventions for BPD treatments, a systematic literature review was conducted with two primary aims: to assess the potential of technological tools to enhance treatment outcomes for individuals with BPD and to examine the associated limitations of these interventions. The review utilized a total of twelve papers sourced from electronic databases and journals including IEEE Xplore, PubMed, JMIR Mental Health Journal, Springer Nature, Research Gate, and Journal of Psychiatric Practice. Authors in these papers explore a variety of technological interventions from the integration of virtual reality technology in enhancing treatments, Dialectical Behavior Therapy (DBT) coach apps for addressing BPD and substance usage issues, the use of image processing techniques in predicting treatment responses, artificial intelligence-based tools, expert systems, and chatbots in identifying the potential and limitations of these interventions. The findings reveal those novel technologies such as virtual reality show potential in therapy skill training. However, despite advancements in artificial intelligence and machine learning, Program-O-based chatbots lack personalization in addressing treatment plans effectively for individuals. Future researchers can be focused on integrating Natural Language Processing into existing interventions for real-time monitoring 2024-01-01T00:00:00Z