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 …

Objective The integration of artificial intelligence (AI) and machine learning (ML) in health
care to aid clinical decisions is widespread. However, as AI and ML take important roles in …

Artificial intelligence systems are increasingly being applied to healthcare. In surgery, AI
applications hold promise as tools to predict surgical outcomes, assess technical skills, or …

Importance Health care algorithms are used for diagnosis, treatment, prognosis, risk
stratification, and allocation of resources. Bias in the development and use of algorithms can …

Background It has been rightfully emphasized that the use of AI for clinical decision making
could amplify health disparities. An algorithm may encode protected characteristics, and …

Background: Clinical artificial intelligence (AI) has reached a critical inflection point.
Advances in algorithmic science and increased understanding of operational considerations …

The exponential growth of big data in RNA biology (RB) has led to the development of deep
learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL …

Background: The use of social media for disseminating health care information has become
increasingly prevalent, making the expanding role of artificial intelligence (AI) and machine …

Objectives Artificial intelligence (AI) systems have the potential to revolutionize clinical
practices, including improving diagnostic accuracy and surgical decision-making, while also …

Artificial Intelligence (AI) has transformed how we live and how we think, and it will change
how we practice medicine. With multimodal big data, we can develop large medical models …