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Predictive diagnostics for early identification of cardiovascular disease: a machine learning approach Cover

Predictive diagnostics for early identification of cardiovascular disease: a machine learning approach

International Journal on Smart Sensing and Intelligent Systems
Volume 18 (2025): Issue 1 (January 2025)
By: Pooja Bagane,  Moksh Oswal,  Sachin Mhetre,  Prabhat Shankar,  Praneet Mahendrakar and  Obsa Amenu Jebessa  
Open Access
|May 2025

Authors

Pooja Bagane

pooja.bagane@gmail.com

Department of Computer Science and Engineering, Symbiosis Institute of Technology – Pune Campus, Symbiosis International (Deemed University), Pune, India

Moksh Oswal

Department of Computer Science and Engineering, Symbiosis Institute of Technology – Pune Campus, Symbiosis International (Deemed University), Pune, India

Sachin Mhetre

Department of Computer Science and Engineering, Symbiosis Institute of Technology – Pune Campus, Symbiosis International (Deemed University), Pune, India

Prabhat Shankar

Department of Computer Science and Engineering, Symbiosis Institute of Technology – Pune Campus, Symbiosis International (Deemed University), Pune, India

Praneet Mahendrakar

Department of Computer Science and Engineering, Symbiosis Institute of Technology – Pune Campus, Symbiosis International (Deemed University), Pune, India

Obsa Amenu Jebessa

Department of Information Technology, Jimma Institute of Technology, Jimma, Ethiopia
DOI: https://doi.org/10.2478/ijssis-2025-0021 | Journal eISSN: 1178-5608
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Language: English
Submitted on: Jan 12, 2025
Published on: May 16, 2025
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
heart disease prediction,
AI,
machine learning,
MLP
Related subjects:
Engineering,
Introductions and overviews,
Engineering, other

© 2025 Pooja Bagane, Moksh Oswal, Sachin Mhetre, Prabhat Shankar, Praneet Mahendrakar, Obsa Amenu Jebessa, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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