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 …
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
A growing number of artificial intelligence (AI)-based clinical decision support systems are
showing promising performance in preclinical, in silico, evaluation, but few have yet …
showing promising performance in preclinical, in silico, evaluation, but few have yet …
[HTML][HTML] SHIFTing artificial intelligence to be responsible in healthcare: A systematic review
H Siala, Y Wang - Social Science & Medicine, 2022 - Elsevier
A variety of ethical concerns about artificial intelligence (AI) implementation in healthcare
have emerged as AI becomes increasingly applicable and technologically advanced. The …
have emerged as AI becomes increasingly applicable and technologically advanced. The …
[HTML][HTML] Addressing fairness in artificial intelligence for medical imaging
A plethora of work has shown that AI systems can systematically and unfairly be biased
against certain populations in multiple scenarios. The field of medical imaging, where AI …
against certain populations in multiple scenarios. The field of medical imaging, where AI …
A call to action on assessing and mitigating bias in artificial intelligence applications for mental health
AC Timmons, JB Duong, N Simo Fiallo… - Perspectives on …, 2023 - journals.sagepub.com
Advances in computer science and data-analytic methods are driving a new era in mental
health research and application. Artificial intelligence (AI) technologies hold the potential to …
health research and application. Artificial intelligence (AI) technologies hold the potential to …
Cross-ethnicity/race generalization failure of behavioral prediction from resting-state functional connectivity
Algorithmic biases that favor majority populations pose a key challenge to the application of
machine learning for precision medicine. Here, we assessed such bias in prediction models …
machine learning for precision medicine. Here, we assessed such bias in prediction models …
Towards Risk‐Free Trustworthy Artificial Intelligence: Significance and Requirements
Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic
decision‐making (DM), these systems have found wide‐ranging applications across diverse …
decision‐making (DM), these systems have found wide‐ranging applications across diverse …
Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences
Machine learning (ML) methodology used in the social and health sciences needs to fit the
intended research purposes of description, prediction, or causal inference. This paper …
intended research purposes of description, prediction, or causal inference. This paper …
A nationwide network of health AI assurance laboratories
Importance Given the importance of rigorous development and evaluation standards
needed of artificial intelligence (AI) models used in health care, nationwide accepted …
needed of artificial intelligence (AI) models used in health care, nationwide accepted …
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 …