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What should medical students know about artificial intelligence in medicine?

Authors
 Seong Ho Park  ;  Kyung-Hyun Do  ;  Sungwon Kim  ;  Joo Hyun Park  ;  Young-Suk Lim 
Citation
 Journal of Educational Evaluation for Health Professions (보건의료교육평가), Vol.16 : 18, 2019 
Journal Title
 Journal of Educational Evaluation for Health Professions (보건의료교육평가) 
ISSN
 1975-5937 
Issue Date
2019
MeSH
Algorithms ; Artificial Intelligence/trends* ; Biostatistics ; Diffusion of Innovation ; Education, Medical ; Evidence-Based Medicine* ; Humans ; Machine Learning/trends* ; Students, Medical*
Keywords
Artificial intelligence ; Deep learning ; Machine learning ; Medical students
Abstract
Artificial intelligence (AI) is expected to affect various fields of medicine substantially and has the potential to improve many aspects of healthcare. However, AI has been creating much hype, too. In applying AI technology to patients, medical professionals should be able to resolve any anxiety, confusion, and questions that patients and the public may have. Also, they are responsible for ensuring that AI becomes a technology beneficial for patient care. These make the acquisition of sound knowledge and experience about AI a task of high importance for medical students. Preparing for AI does not merely mean learning information technology such as computer programming. One should acquire sufficient knowledge of basic and clinical medicines, data science, biostatistics, and evidence-based medicine. As a medical student, one should not passively accept stories related to AI in medicine in the media and on the Internet. Medical students should try to develop abilities to distinguish correct information from hype and spin and even capabilities to create thoroughly validated, trustworthy information for patients and the public.
Files in This Item:
T201905633.pdf Download
DOI
10.3352/jeehp.2019.16.18
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Kim, Sungwon(김성원) ORCID logo https://orcid.org/0000-0001-5455-6926
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/174792
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