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 …
The limits of fair medical imaging AI in real-world generalization
As artificial intelligence (AI) rapidly approaches human-level performance in medical
imaging, it is crucial that it does not exacerbate or propagate healthcare disparities. Previous …
imaging, it is crucial that it does not exacerbate or propagate healthcare disparities. Previous …
Real-world data: a brief review of the methods, applications, challenges and opportunities
F Liu, D Panagiotakos - BMC Medical Research Methodology, 2022 - Springer
Background The increased adoption of the internet, social media, wearable devices, e-
health services, and other technology-driven services in medicine and healthcare has led to …
health services, and other technology-driven services in medicine and healthcare has led to …
The value of standards for health datasets in artificial intelligence-based applications
Artificial intelligence as a medical device is increasingly being applied to healthcare for
diagnosis, risk stratification and resource allocation. However, a growing body of evidence …
diagnosis, risk stratification and resource allocation. However, a growing body of evidence …
[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 …
Machine learning and algorithmic fairness in public and population health
Until now, much of the work on machine learning and health has focused on processes
inside the hospital or clinic. However, this represents only a narrow set of tasks and …
inside the hospital or clinic. However, this represents only a narrow set of tasks and …
Friend or foe? Teaming between artificial intelligence and workers with variation in experience
As artificial intelligence (AI) applications become more pervasive, it is critical to understand
how knowledge workers with different levels and types of experience can team with AI for …
how knowledge workers with different levels and types of experience can team with AI for …
Accessing artificial intelligence for clinical decision-making
C Giordano, M Brennan, B Mohamed… - Frontiers in digital …, 2021 - frontiersin.org
Advancements in computing and data from the near universal acceptance and
implementation of electronic health records has been formative for the growth of …
implementation of electronic health records has been formative for the growth of …
Beyond bias and discrimination: redefining the AI ethics principle of fairness in healthcare machine-learning algorithms
The increasing implementation of and reliance on machine-learning (ML) algorithms to
perform tasks, deliver services and make decisions in health and healthcare have made the …
perform tasks, deliver services and make decisions in health and healthcare have made the …