Artificial Intelligence in Cardiac Disease Diagnosis: A Comprehensive Investigation

Tianhao Zhang

2024

Abstract

In the medical field, the use of massive data to assist medical diagnosis is an inevitable trend of development. In the diagnostic process, various machine learning algorithms are utilized to achieve assisted medical diagnosis of cardiac diseases based on a large amount of data sources acquired in clinical practice. This paper introduces the role of artificial intelligence (AI) in the diagnosis of cardiac diseases, and describes the utilization of various traditional machine learning and deep learning models to improve diagnostic efficiency and accuracy. By examining large amounts of clinical data, including electronic health records and imaging, AI has a unique advantage over traditional diagnostic methods in terms of high accuracy and efficiency. This paper explores a variety of AI diagnostic frameworks. In addition, this paper explores the limitations and challenges faced by AI in the field of medical diagnostics today, including issues of data quality, model interpretability, and population generalization, and also proposes corresponding approaches such as federated learning and Explainable AI are also proposed as possible solutions to overcome these obstacles. This paper not only demonstrates the current progress of AI in the field of cardiac diagnosis, but also makes predictions about its future prospects.

Paper Citation

in Harvard Style

Zhang T. (2024). Artificial Intelligence in Cardiac Disease Diagnosis: A Comprehensive Investigation. In Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-713-9, SciTePress, pages 135-140. DOI: 10.5220/0012911200004508

in Bibtex Style

@conference{emiti24,
author={Tianhao Zhang},
title={Artificial Intelligence in Cardiac Disease Diagnosis: A Comprehensive Investigation},
booktitle={Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2024},
pages={135-140},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012911200004508},
isbn={978-989-758-713-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - Artificial Intelligence in Cardiac Disease Diagnosis: A Comprehensive Investigation
SN - 978-989-758-713-9
AU - Zhang T.
PY - 2024
SP - 135
EP - 140
DO - 10.5220/0012911200004508
PB - SciTePress