医学
人工智能
机器学习
人工智能应用
数据科学
生物统计学
大数据
医疗实践
主题(文档)
医学教育
计算机科学
病理
数据挖掘
公共卫生
万维网
作者
D. Douglas Miller,Eric W. Brown
标识
DOI:10.1016/j.amjmed.2017.10.035
摘要
Abstract
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.
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