Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)

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An Integrated Machine Learning Framework for Heart Attack Prediction and Appointment Scheduling

Authors
Sruthi Suresh1, *, L. Thrishal1, K. Karthikayani1
1Department Of Computer and Engineering, SRM Institute Of Science and Technology, Vadapalani Campus, Chennai, Tamilnadu, India
*Corresponding author. Email: ss4471@srmist.edu.in
Corresponding Author
Sruthi Suresh
Available Online 31 October 2025.
DOI
10.2991/978-94-6463-866-0_40How to use a DOI?
Keywords
Heart Disease Prediction; Machine Learning; Random Forest; Risk Assessment; Appointment Booking System; PDF Data Extraction; Healthcare Automation; Doctor Recommendation System
Abstract

Heart disease is a leading cause of mortality worldwide, highlighting the urgent need for early detection and timely medical intervention. This study introduces an integrated system that leverages machine learning, specifically a Random Forest classifier, to predict heart attack risk based on structured patient health data. The system not only assesses individual risk levels but also recommends appropriate specialists and facilitates appointment booking based on the severity of the prediction. It includes features such as automated data extraction from uploaded medical reports in PDF format and an administrative panel for managing doctor details. Experimental results confirm the system’s high accuracy, reliable specialist suggestions, and user-friendly interface. By combining intelligent prediction with streamlined healthcare access, the platform aims to enhance early diagnosis and patient outcomes. Future enhancements will explore the integration of deep learning models and real-time health monitoring for improved precision and responsiveness.

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 the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
31 October 2025
ISBN
978-94-6463-866-0
ISSN
2589-4919
DOI
10.2991/978-94-6463-866-0_40How 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  - Sruthi Suresh
AU  - L. Thrishal
AU  - K. Karthikayani
PY  - 2025
DA  - 2025/10/31
TI  - An Integrated Machine Learning Framework for Heart Attack Prediction and Appointment Scheduling
BT  - Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)
PB  - Atlantis Press
SP  - 472
EP  - 488
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-866-0_40
DO  - 10.2991/978-94-6463-866-0_40
ID  - Suresh2025
ER  -