无线电技术
医疗保健
底漆(化妆品)
医学
放射科
有机化学
化学
经济
经济增长
作者
Carly E Waldman,Melody Hermel,Jonathan A. Hermel,Francis G. Allinson,Mark N Pintea,Natalie Bransky,Emem Udoh,Laura Nicholson,Austin A. Robinson,Jorge González,Christopher Suhar,Keshav R. Nayak,George E. Wesbey,Sanjeev P. Bhavnani
出处
期刊:Personalized Medicine
[Future Medicine]
日期:2022-07-26
卷期号:19 (5): 445-456
被引量:15
标识
DOI:10.2217/pme-2022-0014
摘要
The application of artificial intelligence (AI) to healthcare has garnered significant enthusiasm in recent years. Despite the adoption of new analytic approaches, medical education on AI is lacking. We aim to create a usable AI primer for medical education. We discuss how to generate a clinical question involving AI, what data are suitable for AI research, how to prepare a dataset for training and how to determine if the output has clinical utility. To illustrate this process, we focused on an example of how medical imaging is employed in designing a machine learning model. Our proposed medical education curriculum addresses AI's potential and limitations for enhancing clinicians' skills in research, applied statistics and care delivery.
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