Discover how AI is transforming urological cancer care with improved diagnosis, personalized treatments, and enhanced patient ...

I lived and worked through the transition in medicine from completely paper-based documentation to completely digital-based - ...

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.

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

Quibim says its longer-term plan is to create digital twins of the entire human body, serving “dynamic models” that help the ...

Prof. Jens Kleesiek from the Institute for Artificial Intelligence in Medicine (IKIM) at University Hospital Essen and the Cancer Research Center Cologne Essen (CCCE) Oncological clinical practice ...

For example, a clinician might ask whether ... researchers can also use these patient records to train AI models for use in medical practice. Superficially, the idea of using patient health ...

There are also ethical issues to consider, including doctor patient confidentiality in the case of surveillance, but more broadly there’s the concern over AI’s programming. If it’s making predictions ...

The final rule regulates the use of patient care decision support tools, including artificial intelligence (AI ... 10 letter provides the following examples: Review OCR's discussion of risks ...

OCR published the final rule interpreting and implementing Section 1557 at 45 C.F.R. § 92 (the Final Rule). The Final Rule ...