Department of Radiodiagnosis, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India.
AJR Am J Roentgenol. 2020 May;214(5):1137-1138. doi: 10.2214/AJR.19.22145. Epub 2020 Mar 4.
The purpose of this article is to discuss the problem of interpretability of artificial intelligence (AI) and highlight the need for continuing scientific discovery using AI algorithms to deal with medical big data. A plethora of AI algorithms are currently being used in medical research, but the opacity of these algorithms makes their clinical implementation a dilemma. Clinical decision making cannot be assigned to something that we do not understand. Therefore, AI research should not be limited to reporting accuracy and sensitivity but, rather, should try to explain the underlying reasons for the predictions, in an attempt to enrich biologic understanding and knowledge.
本文旨在探讨人工智能（AI）的可解释性问题，并强调需要继续使用 AI 算法进行科学发现，以处理医疗大数据。目前，大量的 AI 算法正在被应用于医学研究中，但这些算法的不透明性使得它们在临床实施上面临困境。我们不能将临床决策交给我们不理解的东西。因此，人工智能研究不应仅限于报告准确性和敏感性，而应尝试解释预测的潜在原因，试图丰富生物学理解和知识。
