Advancements in Communication and Systems
Exploring the Role of Machine Learning in Disease Diagnosis via Body Signals: An Extensive Review
Authors: Garima Mathur, Shweta Singh, Shumali Gupta, Priyanka Singh, Bhavna Soni and Jai Mungi
Publishing Date: 12-02-2024
ISBN: 978-81-955020-7-3
Abstract
Heart disease is one of the most serious human diseases, with devastating consequences. In cardiac disease, the heart is unable to pump enough blood to the rest of the body. Accurate and timely heart disease diagnosis is critical for heart failure prevention and treatment. Traditional medical history diagnosis of heart disease has been deemed untrustworthy in several ways. Noninvasive methods, such as machine learning, are reliable and effective for classifying healthy people and persons with cardiac disease. Based on relevant research, this review covers the use of machine learning in the early detection of various diseases. The study then summarizes the most recent achievements in the field of machine learning-driven identification of diseases and Telemedicine, taking into account the algorithm, different disease categories, various body signals, numerous applications, and various assessment metrics. Finally, we summarize the key findings.
Keywords
Diagnosis, Machine learning (ML), Disease detection, Tele-medicine.
Cite as
Garima Mathur, Shweta Singh, Shumali Gupta, Priyanka Singh, Bhavna Soni and Jai Mungi, "Exploring the Role of Machine Learning in Disease Diagnosis via Body Signals: An Extensive Review", In: Ashish Kumar Tripathi and Vivek Shrivastava (eds), Advancements in Communication and Systems, SCRS, India, 2024, pp. 185-195. https://doi.org/10.56155/978-81-955020-7-3-17