Back to Search Start Over

Research on Artificial-Intelligence-Assisted Medicine: A Survey on Medical Artificial Intelligence.

Authors :
Gou, Fangfang
Liu, Jun
Xiao, Chunwen
Wu, Jia
Source :
Diagnostics (2075-4418); Jul2024, Vol. 14 Issue 14, p1472, 52p
Publication Year :
2024

Abstract

With the improvement of economic conditions and the increase in living standards, people's attention in regard to health is also continuously increasing. They are beginning to place their hopes on machines, expecting artificial intelligence (AI) to provide a more humanized medical environment and personalized services, thus greatly expanding the supply and bridging the gap between resource supply and demand. With the development of IoT technology, the arrival of the 5G and 6G communication era, and the enhancement of computing capabilities in particular, the development and application of AI-assisted healthcare have been further promoted. Currently, research on and the application of artificial intelligence in the field of medical assistance are continuously deepening and expanding. AI holds immense economic value and has many potential applications in regard to medical institutions, patients, and healthcare professionals. It has the ability to enhance medical efficiency, reduce healthcare costs, improve the quality of healthcare services, and provide a more intelligent and humanized service experience for healthcare professionals and patients. This study elaborates on AI development history and development timelines in the medical field, types of AI technologies in healthcare informatics, the application of AI in the medical field, and opportunities and challenges of AI in the field of medicine. The combination of healthcare and artificial intelligence has a profound impact on human life, improving human health levels and quality of life and changing human lifestyles. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20754418
Volume :
14
Issue :
14
Database :
Complementary Index
Journal :
Diagnostics (2075-4418)
Publication Type :
Academic Journal
Accession number :
178689191
Full Text :
https://doi.org/10.3390/diagnostics14141472