Robotics & Machine Learning Daily News2024,Issue(Nov.28) :21-21.

Duke-National University of Singapore Medical School Reports Findings in Machine Learning (FAIM: Fairness-aware interpretable modeling for trustworthy machine l earning in healthcare)

新加坡国立大学医学院报告机器学习的发现(FAIM:公平感知可解释医疗保健领域可信机器收益建模

Robotics & Machine Learning Daily News2024,Issue(Nov.28) :21-21.

Duke-National University of Singapore Medical School Reports Findings in Machine Learning (FAIM: Fairness-aware interpretable modeling for trustworthy machine l earning in healthcare)

新加坡国立大学医学院报告机器学习的发现(FAIM:公平感知可解释医疗保健领域可信机器收益建模

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-机器学习的新研究是一篇报道的主题。据新闻报道NewsRx记者在新加坡的报道,Research称,“不断升级的一体化,包括医疗保健等高风险领域的机器学习引起了人们对模型公平性的极大关注。我们提出了一个可解释的框架,公平感知的可解释模型(FAIM),以改进模型在不影响性能的情况下实现公平,采用交互式界面来确定“更公平”的模式从一套高性能模型出发促进数据驱动证据与临床证据的整合加强背景公平的专业知识"。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsreporting from Singapore, Singapore, by NewsRx journalists, research stated, “The escalating integration ofmachine lea rning in high-stakes fields such as healthcare raises substantial concerns about model fairness.We propose an interpretable framework, fairness-aware interpret able modeling (FAIM), to improve modelfairness without compromising performance , featuring an interactive interface to identify a ‘fairer’ modelfrom a set of high-performing models and promoting the integration of data-driven evidence and clinicalexpertise to enhance contextualized fairness.”

Key words

Singapore/Singapore/Asia/Cyborgs/Eme rging Technologies/Hospitals/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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