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Identifying and mitigating bias in machine learning models used in population health

Identifying and mitigating bias in machine learning models used in population health
识别和减轻人口健康中使用的机器学习模型中的偏差
批准号：
442938
负责人：
Pinto Andrew D
金额：
$7.29万
依托单位：
Unity Health Toronto
依托单位国家：
加拿大
项目类别：
Operating Grants
财政年份：
2020
资助国家：
加拿大
项目状态：
已结题
起止时间：
2020-10-01 至 2021-10-01
来源：
https://webapps.cihr-irsc.gc.ca/decisions/p/project_details.html?applId=442938&lang=en
关键词：
Artificial Intelligence Bias Equity Guideline Development Health Inequities Machine Learning Model Development Population Health Public Health

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中文摘要
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英文摘要
Machine learning (ML) is a form of artificial intelligence that has increasingly been used over the last decade in a variety of sectors, as computing power and the availability of data has increased exponentially. ML applies algorithms to vast amounts of
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