医学
个性化医疗
领域(数学)
替代医学
人工智能
医疗保健
精密医学
数据科学
医学教育
梅德林
生物信息学
计算机科学
病理
生物
经济
法学
纯数学
经济增长
数学
政治学
作者
Guy Handelman,Hong Kuan Kok,Ronil V. Chandra,Amir H. Razavi,M J Lee,Hamed Asadi
摘要
Abstract Machine learning ( ML ) is a burgeoning field of medicine with huge resources being applied to fuse computer science and statistics to medical problems. Proponents of ML extol its ability to deal with large, complex and disparate data, often found within medicine and feel that ML is the future for biomedical research, personalized medicine, computer‐aided diagnosis to significantly advance global health care. However, the concepts of ML are unfamiliar to many medical professionals and there is untapped potential in the use of ML as a research tool. In this article, we provide an overview of the theory behind ML , explore the common ML algorithms used in medicine including their pitfalls and discuss the potential future of ML in medicine.
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