Exploring the Use of Machine Learning in Healthcare

DOI

10.2991/978-94-6463-540-9_21How to use a DOI?

Keywords

Machine Learning; Healthcare; Personalized Medicine; Medical Diagnostics

Abstract

The rapid advancement of machine learning (ML) technologies offers unprecedented opportunities to enhance healthcare diagnostics and treatment, particularly in the face of global challenges such as aging populations and the rise of chronic diseases. This paper explores the transformative impact of ML in medical imaging and disease management, emphasizing its potential to revolutionize personalized medicine, and exploring the application of machine learning in diagnosing and treating various diseases, ranging from cardiovascular diseases to cancer. The paper concludes that machine learning algorithms can significantly enhance the accuracy of medical diagnoses and the personalization of treatment plans. For instance, deep learning has been shown to enhance the detection of subtle abnormalities in medical imaging. At the same time, predictive modeling facilitates the early diagnosis and management of chronic diseases by analyzing patterns in large datasets. The findings underscore that ML increases the efficiency and effectiveness of healthcare services and reduces disease burden through earlier interventions and more tailored treatment strategies. By decreasing the reliance on invasive procedures and minimizing adverse reactions, ML contributes to better patient outcomes and lower healthcare costs. This study can serve as a reference for ongoing collaboration between scientists, clinicians, and policymakers to ensure that these technologies are developed and implemented ethically and effectively, thereby maximizing their benefits in a global health context.

Copyright

© 2024 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.

Download article (PDF)

TY  - CONF
AU  - Shaoyu Yan
PY  - 2024
DA  - 2024/10/16
TI  - Exploring the Use of Machine Learning in Healthcare
BT  - Proceedings of the 2024 2nd International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2024)
PB  - Atlantis Press
SP  - 183
EP  - 190
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-540-9_21
DO  - 10.2991/978-94-6463-540-9_21
ID  - Yan2024
ER  -