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Publication Open Access Personalized Health Monitoring System to Track and Visualize Serum Creatinine Levels of Chronic Kidney Disease Patients: Creatinine Care(SLIIT City UNI, 2025-07-08) Fernando, N.R.T; Jayaweera, Y.DCreatinine Care is a mobile application developed to monitor and manage serum creatinine levels in chronic kidney disease patients. Chronic kidney disease is a significant global health issue affecting both adults and children. Many patients are unaware of their kidney health status, leading to sudden spikes in creatinine levels and emergency hospitalizations. Serum creatinine is a critical biomarker used in estimating kidney function, particularly through the glomerular filtration rate formula. However, most existing kidney-related applications focus on general awareness, basic health tracking, and diet plans, without offering specific creatinine-level monitoring or paediatric support. This application addresses these gaps by offering a dedicated platform for both adult and child kidney patients to track creatinine levels over time. Key features include digital report storage, automated data extraction, visual trend analysis, checkup reminders, and personalized recommendations based on the base creatinine level. The system is developed using React Native with Expo Go for the frontend and SQLite for local storage. A Node.js Express backend supports Optical Character Recognition through Tesseract.js for extracting data from scanned reports. Evaluation involved user acceptance testing and text extraction accuracy testing. The Optical Character Recognition achieved a word-level accuracy of 93.33% on high-quality images and 76.92% on low-quality images, with an overall upload success rate above 86%. The results demonstrate the system's effectiveness in reducing manual data entry, improving patient awareness, and supporting real-time monitoring. Creatinine Care introduces a novel, allin- one digital tool for personalized chronic kidney disease management in paediatric and adult patients.Publication Embargo Prediction of CKDu using KDQOL score, Ankle Swelling and Risk Factor Analysis using Neural Networks(2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Lokuarachchi, D.N.; Manoj, J.V.T.; Weerasooriya, M.N.H.; Waseem, M.N.M.; Aslam, F.; Kumarasinghe, N.; Kasthurirathne, D.Chronic Kidney disease (Chronic Kidney Disease (CKD)) is a type of kidney disease where gradual loss of kidney function occurs over a period of months to years. But, when CKD cannot identify a manner or causation of the disease or set of causes it is known as Chronic Kidney disease with unknown etiology (CKDu). There are several factors to be considered when analyzing the main causes for CKDu such as socio-economic, environmental, meteorological and health aspects in relation to the CKDu in Sri Lanka. In this research work, identification of CKDu has been done using the relationship of the Kidney Disease Quality of Life (KDQOL) score, ankle swelling with the serum creatinine level of blood and considering risk factors. This research has been done using three major branches of Artificial Intelligence namely neural networks, convolutional neural networks and machine learning. The relationship between the mentioned factors and CKDu has been identified. The sensitivity of 77.27% and a specificity of 89.28% have been marked for the detection of CKDu related to ankle swelling.