The words “artificial intelligence” are now ubiquitous, their influence having risen dramatically in recent years and their ...

Bias is a recurring theme in Hofmann’s analysis. He emphasizes that while AI systems can perpetuate and even amplify biases, ...

The hype surrounding AI remains prevalent in healthcare but is particularly strong in radiology. If you remember the early days of computer-aided design (CAD), it’s quite impressive how far the ...

While AI will not replace doctors, it will undoubtedly change how we practice medicine by handling repetitive tasks and augmenting clinical decision making. For example, AI can support diagnostic ...

There is still progress to be made in optimising AI for the unique needs of the medical field. For example, maintaining confidentiality of pre-launch or patient data is a major consideration.

Dr. Pinero de Plaza, research fellow, Flinders' Caring Futures Institute Published in the International Journal of Medical Informatics, the study used PROLIFERATE_AI to assess the RAPIDx AI tool ...

The final rule regulates the use of patient care decision support tools, including artificial intelligence (AI) algorithms ...

DNNs, while highly effective in tasks such as melanoma detection and cardiovascular disease prediction, often rely on ...

A collaborative study between researchers from the Yong Loo Lin School of Medicine, National University of Singapore (NUS ...

The Final Rule regulates the use of patient care decision support tools, including AI algorithms for screening ... 10 letter provides the following examples: Review OCR's discussion of risks ...