Contextualized interpretable machine learning for medical diagnosis
نویسندگان
چکیده
منابع مشابه
Making machine learning models interpretable
Data of different levels of complexity and of ever growing diversity of characteristics are the raw materials that machine learning practitioners try to model using their wide palette of methods and tools. The obtained models are meant to be a synthetic representation of the available, observed data that captures some of their intrinsic regularities or patterns. Therefore, the use of machine le...
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The theoretical novelty of many machine learning methods leading to high performing algorithms has been substantial. However, the black-box nature of much of this body of work has meant that the models are difficult to interpret, with the consequence that the significant developments in machine learning theory are not matched by their practical impact. This tutorial stresses the need for interp...
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ژورنال
عنوان ژورنال: Communications of the ACM
سال: 2020
ISSN: 0001-0782,1557-7317
DOI: 10.1145/3416965