Excellence in a wide variety of medical applications poses considerable challenges for AI,
requiring advanced reasoning, access to up-to-date medical knowledge and understanding …

Abstract Introduction Artificial Intelligence (AI) algorithms, particularly Deep Learning (DL)
models are known to be data intensive. This has increased the demand for digital data in all …

As early as 1979, authors evoked the promise of Artificial Intelligence (AI) to provide
diagnostic and therapeutic recommendations for patients in the intensive care unit (ICU)[1] …

Artificial intelligence (AI) and machine learning (ML) have potential to revolutionize
emergency medical care by enhancing triage systems, improving diagnostic accuracy …

The debate about fairness of artificial intelligence (AI) in health care is gaining momentum.
At present, the focus of the debate is on identifying unfair outcomes resulting from biased …

This retrospective study evaluated a commercial deep learning (DL) software for chest
radiographs and explored its performance in different scenarios. A total of 477 patients (284 …

Background Facial appearance, whether consciously or subconsciously assessed, may
affect clinical assessment and treatment strategies in the Intensive Care Unit (ICU) …

The recent literature on the fairness of AI in health almost exclusively bases AI fairness on
the ethical principle of" equality". This leads us to the insight that" equality" may not be an …

This study looks into the critical discussion surrounding the ethical regulation and
explainability of generative artificial intelligence (AI). Amidst the rapid advancement of …