Algorithmic fairness in artificial intelligence for medicine and healthcare
In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
Mitigating Racial And Ethnic Bias And Advancing Health Equity In Clinical Algorithms: A Scoping Review: Scoping review examines racial and ethnic bias in clinical …
In August 2022 the Department of Health and Human Services (HHS) issued a notice of
proposed rulemaking prohibiting covered entities, which include health care providers and …
proposed rulemaking prohibiting covered entities, which include health care providers and …
Use of Artificial Intelligence in Improving Outcomes in Heart Disease: A Scientific Statement From the American Heart Association
A major focus of academia, industry, and global governmental agencies is to develop and
apply artificial intelligence and other advanced analytical tools to transform health care …
apply artificial intelligence and other advanced analytical tools to transform health care …
A comparison of approaches to improve worst-case predictive model performance over patient subpopulations
Predictive models for clinical outcomes that are accurate on average in a patient population
may underperform drastically for some subpopulations, potentially introducing or reinforcing …
may underperform drastically for some subpopulations, potentially introducing or reinforcing …
The impact of health care algorithms on racial and ethnic disparities: a systematic review
SM Siddique, K Tipton, B Leas, C Jepson… - Annals of Internal …, 2024 - acpjournals.org
Background: There is increasing concern for the potential impact of health care algorithms
on racial and ethnic disparities. Purpose: To examine the evidence on how health care …
on racial and ethnic disparities. Purpose: To examine the evidence on how health care …
Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare
A growing body of work uses the paradigm of algorithmic fairness to frame the development
of techniques to anticipate and proactively mitigate the introduction or exacerbation of health …
of techniques to anticipate and proactively mitigate the introduction or exacerbation of health …
Artificial Intelligence for Cardiovascular Care—Part 1: Advances: JACC Review Topic of the Week
P Elias, SS Jain, T Poterucha, M Randazzo… - Journal of the American …, 2024 - jacc.org
Recent artificial intelligence (AI) advancements in cardiovascular care offer potential
enhancements in diagnosis, treatment, and outcomes. Innovations to date focus on …
enhancements in diagnosis, treatment, and outcomes. Innovations to date focus on …
Health equity assessment of machine learning performance (HEAL): a framework and dermatology AI model case study
Background Artificial intelligence (AI) has repeatedly been shown to encode historical
inequities in healthcare. We aimed to develop a framework to quantitatively assess the …
inequities in healthcare. We aimed to develop a framework to quantitatively assess the …
[HTML][HTML] A scoping review of fair machine learning techniques when using real-world data
Objective The integration of artificial intelligence (AI) and machine learning (ML) in health
care to aid clinical decisions is widespread. However, as AI and ML take important roles in …
care to aid clinical decisions is widespread. However, as AI and ML take important roles in …
The American Society for Bone and Mineral Research Task Force on clinical algorithms for fracture risk report
Using race and ethnicity in clinical algorithms potentially contributes to health inequities. The
American Society for Bone and Mineral Research (ASBMR) Professional Practice …
American Society for Bone and Mineral Research (ASBMR) Professional Practice …