Artificial Intelligence in Medical Practice: The Question to the Answer?

被引:370
|
作者
Miller, D. Douglas [1 ]
Brown, Eric W. [2 ]
机构
[1] New York Med Coll, Valhalla, NY 10595 USA
[2] IBM Watson Hlth, Fdn Innovat, Yorktown Hts, NY USA
关键词
Analytics; Artificial intelligence; Big data; Chronic disease; Deep learning; Electronic medical record; Machine learning; Medical imaging; Natural language processing; Neural networks; Precision medicine; LEARNING ALGORITHM; DEEP;
D O I
10.1016/j.amjmed.2017.10.035
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Computer science advances and ultra-fast computing speeds find artificial intelligence (AI) broadly benefitting modern society-forecasting weather, recognizing faces, detecting fraud, and deciphering genomics. AI's future role in medical practice remains an unanswered question. Machines (computers) learn to detect patterns not decipherable using biostatistics by processing massive datasets (big data) through layered mathematical models (algorithms). Correcting algorithm mistakes (training) adds to AI predictive model confidence. AI is being successfully applied for image analysis in radiology, pathology, and dermatology, with diagnostic speed exceeding, and accuracy paralleling, medical experts. While diagnostic confidence never reaches 100%, combining machines plus physicians reliably enhances system performance. Cognitive programs are impacting medical practice by applying natural language processing to read the rapidly expanding scientific literature and collate years of diverse electronic medical records. In this and other ways, AI may optimize the care trajectory of chronic disease patients, suggest precision therapies for complex illnesses, reduce medical errors, and improve subject enrollment into clinical trials. (c) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:129 / 133
页数:5
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