Understanding and training for the impact of large language models and artificial intelligence in healthcare practice: a narrative review

被引：1

作者：

McCoy, Liam G. ^{[1
]}

Ci Ng, Faye Yu ^{[2
]}

Sauer, Christopher M. ^{[3
,4
]}

Legaspi, Katelyn Edelwina Yap ^{[5
,6
]}

Jain, Bhav ^{[4
]}

Gallifant, Jack ^{[4
,7
]}

McClurkin, Michael ^{[8
]}

Hammond, Alessandro ^{[9
,10
]}

Goode, Deirdre ^{[11
]}

Gichoya, Judy ^{[12
]}

Celi, Leo Anthony ^{[4
]}

机构：

[1] Univ Alberta, Fac Med & Dent, Edmonton, AB, Canada

[2] Natl Univ Singapore, Yong Loo Lin Sch Med, Singapore, Singapore

[3] Univ Hosp Essen, Inst Artificial Intelligence Med, Essen, Germany

[4] MIT, Lab Computat Physiol, Cambridge, MA 02139 USA

[5] Harvard TH Chan Sch Publ Hlth, Dept Biostat, Boston, MA USA

[6] Univ Philippines Manila, Coll Med, Manila, Philippines

[7] Guys & St ThomasNHS Fdn Trust, Dept Crit Care, London, England

[8] Yale Sch Med, Dept Psychiat, New Haven, CT USA

[9] Harvard Univ, Cambridge, MA USA

[10] Boston Childrens Hosp, Dept Pediat Oncol, Div Hematol Oncol, Boston, MA USA

[11] Beth Israel Deaconess Med Ctr, Dept Emergency Med, Boston, MA USA

[12] Emory Sch Med, Dept Radiol, Atlanta, GA USA

来源：

BMC MEDICAL EDUCATION | 2024年 / 24卷 / 01期

关键词：

Language Model; Medical Education; Technology; Ethics;

D O I：

10.1186/s12909-024-06048-z

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

Reports of Large Language Models (LLMs) passing board examinations have spurred medical enthusiasm for their clinical integration. Through a narrative review, we reflect upon the skill shifts necessary for clinicians to succeed in an LLM-enabled world, achieving benefits while minimizing risks. We suggest how medical education must evolve to prepare clinicians capable of navigating human-AI systems.

引用

页数：8

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