Take Two Aspirin

Gary Smith
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Abstract

IBM’s Watson got an avalanche of publicity when it won Jeopardy, but Watson is potentially far more valuable as a massive digital database for doctors, lawyers, and other professionals who can benefit from fast, accurate access to information. A doctor who suspects that a patient may have a certain disease can ask Watson to list the recognized symptoms. A doctor who notices several abnormalities in a patient, but isn’t confident about which diseases are associated with these symptoms, can ask Watson to list the possible diseases. A doctor who is convinced that a patient has a certain illness can ask Watson to list the recommended treatments. In each case, Watson can make multiple suggestions, with associated probabilities and hyperlinks to the medical records and journal articles that it relied on for its recommendations. Watson and other computerized medical data bases are valuable resources that take advantage of the power of computers to acquire, store, and retrieve information. There are caveats though. One is simply that a medical data base is not nearly as reliable as a Jeopardy data base. Artificial intelligence algorithms are very good at finding patterns in data, but they are very bad at assessing the reliability of the data and the plausibility of a statistical analysis. It could end tragically if a doctor entered a patient’s symptoms into a black-box data-mining program and was told what treatments to use, without any explanation for the diagnosis or prescription. Think for a moment about your reaction if your doctor said, I don’t know why you are ill, but my computer says, “Take these pills.” I don’t know why you are ill, but my computer recommends surgery. Any medical software that uses neural networks or data reduction programs, such as principal components and factor analysis, will be hard-pressed to provide an explanation for the diagnosis and prescribed treatment. Patients won’t know. Doctors won’t know. Even the software engineers who created the black-box system won’t know. Nobody knows. Watson and similar programs are great as a reference tool, but they are not a substitute for doctors because: (a) the medical literature is often wrong; and (b) these errors are compounded by the use of data-mining software.
吃两片阿司匹林
IBM的沃森在赢得《危险边缘》(Jeopardy)后获得了铺天盖地的宣传,但沃森作为一个庞大的数字数据库,对医生、律师和其他专业人士来说可能更有价值,因为他们可以从快速、准确的信息获取中受益。怀疑病人可能患有某种疾病的医生可以让沃森列出已识别的症状。如果医生注意到病人身上出现了一些异常,但不确定哪些疾病与这些症状有关,他可以让沃森列出可能的疾病。如果医生确信病人患有某种疾病,可以让沃森列出推荐的治疗方法。在每种情况下,沃森都可以提出多种建议,并提供相关的概率和超链接,以提供建议所依赖的医疗记录和期刊文章。沃森和其他计算机化的医疗数据库是宝贵的资源,它们利用计算机的能力来获取、存储和检索信息。不过也有一些警告。一个原因很简单,医疗数据库远不如《危险边缘》数据库可靠。人工智能算法非常擅长发现数据中的模式,但它们在评估数据的可靠性和统计分析的合理性方面非常糟糕。如果医生将病人的症状输入一个黑匣子数据挖掘程序,并被告知使用什么治疗方法,而没有任何诊断或处方的解释,这可能会以悲剧告终。想象一下,如果你的医生说,我不知道你为什么生病,但我的电脑说,“吃这些药。”我不知道你为什么病了,但我的电脑建议你做手术。任何使用神经网络或数据简化程序(如主成分和因素分析)的医疗软件都将很难为诊断和处方治疗提供解释。病人不会知道的。医生不会知道的。即使是创建黑盒系统的软件工程师也不会知道。没有人知道。沃森和类似的程序是很好的参考工具,但它们不能代替医生,因为:(a)医学文献经常是错误的;(b)数据挖掘软件的使用使这些错误更加复杂。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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