Explore the Current Application Status of Machine Learning in the Medical Field

College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, 210016, Nanjing, China

^* Corresponding author: zz23002@nuaa.edu.cn

Abstract

The application of machine learning in the medical field can improve the quality and efficiency of medical services and promote the innovative development of healthcare. However, there are still many shortcomings in the development of related fields. This paper explores the current development status of machine learning technology and its application in the medical field and explores the direction of its future development and the defects that can be improved, mainly through the literature research method. This paper finds that many current studies lack mature large-scale datasets as training materials. Similarly, the trained models lack applications in real-world scenarios to validate their prediction or detection performance, and can only be verified in other existing datasets, which requires wider collaboration to enable and improve them. The significance of this study mainly lies in sorting out the current development status of machine learning applications in the medical field in China, illustrating the breadth and limitations of the current applications of AI in the medical field, and providing references and guidance for the future development of related fields.