Open your black box classifier
IF 2.8
Q3 ENGINEERING, BIOMEDICAL
引用次数: 0
Abstract
A priority for machine learning in healthcare and other high stakes applications is to enable end-users to easily interpret individual predictions. This opinion piece outlines recent developments in interpretable classifiers and methods to open black box models.
打开黑盒分类器
在医疗保健和其他高风险应用中，机器学习的首要任务是使最终用户能够轻松地解释个人预测。这篇观点文章概述了可解释分类器和打开黑盒模型的方法的最新发展。
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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来源期刊
Healthcare Technology Letters
Health Professions-Health Information Management
CiteScore
6.10
自引率
4.80%
发文量
12
审稿时长
22 weeks
期刊介绍：
Healthcare Technology Letters aims to bring together an audience of biomedical and electrical engineers, physical and computer scientists, and mathematicians to enable the exchange of the latest ideas and advances through rapid online publication of original healthcare technology research. Major themes of the journal include (but are not limited to): Major technological/methodological areas: Biomedical signal processing Biomedical imaging and image processing Bioinstrumentation (sensors, wearable technologies, etc) Biomedical informatics Major application areas: Cardiovascular and respiratory systems engineering Neural engineering, neuromuscular systems Rehabilitation engineering Bio-robotics, surgical planning and biomechanics Therapeutic and diagnostic systems, devices and technologies Clinical engineering Healthcare information systems, telemedicine, mHealth.
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