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Dr. K. N. Venkata Ratna Kumar is a Professor in the Department of Computer Science and Engineering at Lingayas Institute of Management and Technology, Nunna, Vijayawada, Andhra Pradesh, India. His academic responsibilities include teaching and research in computer science and engineering. His professional role contributes to higher education in computing technologies. His chapter contribution focuses on machine learning-based kidney disease prediction and clinical decision support.
Renal illness represents a major worldwide health issue characterised by the gradual decline of kidney function, heightened cardiovascular risk, increased hospital admissions, and diminished quality of life. Chronic kidney disease (CKD) can progress slowly and often goes unnoticed in its initial phases, highlighting the necessity for prompt detection and suitable clinical oversight. This chapter explores the function of machine learning in forecasting renal illness, encompassing data collection, preprocessing, feature selection, model creation, assessment, interpretable artificial intelligence, and clinical decision assistance. A suggested framework is introduced for combining predictive modelling with personalised risk assessment, clinician-oriented explanations, and suitable follow-up procedures. The section additionally addresses data integrity, model adjustment, equitable algorithms, confidentiality, clinical verification, and implementation obstacles. Accurately verified machine learning algorithms can assist in identifying patients needing additional assessment, facilitate the monitoring of renal function, and enhance clinical decision-making. Predictive models should augment existing diagnostic standards and expert assessment instead of supplanting them.