A Survey on Machine Learning, Its Approaches and Challenges in Health Care

Pallavi Sood

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024, vol. 10, issue 6, 167-175

Abstract: The area of machine learning research is constantly growing, offering several opportunities for investigation and application. ML is widely utilized in various applications like finance, life science, health care, transportation, education, security etc. The health care sector has long been an early adopter of and benefited greatly from technological advances. These days, machine learning plays a key role in many health related realms, including the development of new medical procedures, the handling of patient data and records, the treatment of chronic diseases, the findings of effects of various medicines, to discover patterns from medical data sources and provide excellent capabilities to predict diseases etc. An overview of machine learning-based approaches, learning algorithms, and applications in several healthcare domains is given in this study.

Keywords: Machine Learning; Healthcare; Artificial Intelligence; Applications; Approaches (search for similar items in EconPapers)
Date: 2024
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT2410438
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ijsrcseit.com/home/article/view/CSEIT2410438 Article URL (text/html)
https://ijsrcseit.com/home/article/download/CSEIT2410438/CSEIT2410438 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v10:y2024:i6:id:405

DOI: 10.32628/CSEIT2410438

Access Statistics for this article

More articles in International Journal of Scientific Research in Computer Science, Engineering and Information Technology from International Journal of Scientific Research in Computer Science, Engineering and Information Technology
Bibliographic data for series maintained by Pankaj Sharma ().