Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)

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Cardio Disease Prediction Using ML

Authors
K. Deniel Raju1, M. Santosh Bhargav1, *, P. Deepika1, A. Jaswanth Manohar1, J. Dinesh Reddy1
1Department of Information Technology, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, India
*Corresponding author. Email: madabattulasantoshbhargav.21.it@anits.edu.in
Corresponding Author
M. Santosh Bhargav
Available Online 4 November 2025.
DOI
10.2991/978-94-6463-858-5_270How to use a DOI?
Keywords
cardiovascular conditions (CVDs); forecasting heart disease; artificial intelligence (AI); machine learning; risk evaluation; medical background; lifestyle variables
Abstract

Cardiovascular diseases (CVDs) pose a significant worldwide health issue, and early prevention and detection are therefore critical to lowering mor- tality. This heart disease prediction app relies on sophisticated machine learn-ing techniques to assess an individual’s risk level against vital health param-eters such as blood pressure, cholesterol, heart rate, BMI, diabetes status, and life- style. Through real-time analysis of this information, the app provides users with a true risk assessment and customized health information to enable them to make educated choices regarding their well-being. The app provides tailored advice on eating habits, exercise, and medical consultations, empowering individuals to take proactive action for heart health. The app also enables smooth integration of data with healthcare professionals to monitor continuously and improve clinical decision-making. Outside of cardiovascular wellness, AI-based breakthroughs are also re-shaping transport safety through prevention of sleepy driving hazards, to the greater public good. By using forecasting analytics and re-al-time monitor- ing, the tech has the objective of reducing undiag-nosed heart conditions preva- lence and encouraging an early intervention for disease prevention.

Copyright
© 2025 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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Volume Title
Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
Series
Advances in Computer Science Research
Publication Date
4 November 2025
ISBN
978-94-6463-858-5
ISSN
2352-538X
DOI
10.2991/978-94-6463-858-5_270How to use a DOI?
Copyright
© 2025 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.

Cite this article

risenwbib
TY  - CONF
AU  - K. Deniel Raju
AU  - M. Santosh Bhargav
AU  - P. Deepika
AU  - A. Jaswanth Manohar
AU  - J. Dinesh Reddy
PY  - 2025
DA  - 2025/11/04
TI  - Cardio Disease Prediction Using ML
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 3244
EP  - 3251
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_270
DO  - 10.2991/978-94-6463-858-5_270
ID  - Raju2025
ER  -