E-Medical Insight: Heart and Chronic Kidney Diseases Classification and Prediction

DOI

10.2991/978-94-6239-693-7_111How to use a DOI?

Keywords

Heart Disease Prediction; Chronic Kidney Disease; Machine Learning; Medical Data Analytics; Disease Classification; Clinical Decision Support

Abstract

It is an intelligent framework of the prediction and classification of heart disease and dynamic kidney disease by implementing advanced machine learning techniques. Both cardiovascular and renal diseases fall under the list of common causes of morbidity and mortality on the planet, and are likely to progress without any noticeable symptoms, before their severe complications manifest. It is therefore necessary to predict and make correct decisions in time and make positive clinical decisions. The proposed system looks at the records of the patient health which consist of demographical records, clinical measurements, and laboratory tests among others to determine the disease trends. Data preprocessing like cleaning of data, normalization and selection of the features is the process which is applied so that data is improved in quality and reliability of the model. A number of machine learning classifier are performed and tested to define their predictive capabilities. The framework supports the timely diagnosis of the disease, reduces the application of manual assessment, and enhances clinical performance. Through combined insights of data and medical decision support, the proposed solution will result in improved patient outcomes and can be applied as a large-scale solution to intelligent healthcare monitoring and detection of diseases.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Manju C. Nair
AU  - R. Yelvizhi
AU  - V. Bhagyasree
AU  - K. Dhanalakshmi
AU  - Bandey Y. S. C. Nitheesh
AU  - V. Asha Judi
PY  - 2026
DA  - 2026/06/16
TI  - E-Medical Insight: Heart and Chronic Kidney Diseases Classification and Prediction
BT  - Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026)
PB  - Atlantis Press
SP  - 1156
EP  - 1165
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-693-7_111
DO  - 10.2991/978-94-6239-693-7_111
ID  - Nair2026
ER  -