Nichols James A, Herbert Chan Hsien W, Baker Matthew A B
Laboratoire Jacques-Louis Lions, Sorbonne Université, Paris, France.
Centenary Institute, The University of Sydney, Sydney, Australia.
Biophys Rev. 2019 Feb;11(1):111-118. doi: 10.1007/s12551-018-0449-9. Epub 2018 Sep 4.
Machine learning (ML) is a form of artificial intelligence which is placed to transform the twenty-first century. Rapid, recent progress in its underlying architecture and algorithms and growth in the size of datasets have led to increasing computer competence across a range of fields. These include driving a vehicle, language translation, chatbots and beyond human performance at complex board games such as Go. Here, we review the fundamentals and algorithms behind machine learning and highlight specific approaches to learning and optimisation. We then summarise the applications of ML to medicine. In particular, we showcase recent diagnostic performances, and caveats, in the fields of dermatology, radiology, pathology and general microscopy.
机器学习（ML）是人工智能的一种形式，有望变革21世纪。其基础架构、算法最近取得的快速进展以及数据集规模的增长，已使计算机在一系列领域的能力不断增强。这些领域包括驾驶车辆、语言翻译、聊天机器人，以及在诸如围棋等复杂棋盘游戏中超越人类表现。在此，我们回顾机器学习背后的基本原理和算法，并强调学习与优化的具体方法。然后，我们总结机器学习在医学中的应用。特别是，我们展示了其在皮肤病学、放射学、病理学和普通显微镜检查领域的近期诊断性能及注意事项。
