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The measurement of attitudes toward the implementation of an electronic medical record could help in planning the implementation process and schedule. For example, rollou [...]

The FDA has received millions of reports of adverse events over the last ten years. A clinician's ability to identify potential drug-drug interactions in routine practice [...]

Concern about safety and, likewise, errors in medicine exploded after the first Institute of Medicine report “To Err is Human: building a safer health system” in 1999. (1 [...]

Algorithmic bias refers to the biases originating from the use of artificial intelligence (AI). With AI being increasingly used in healthcare, clinicians need to be able [...]

Antimicrobial resistance AR is a serious clinical and public health problem driven largely by inappropriate use of antimicrobials particularly in the setting of empiric t [...]

Glaucoma is a group of chronic and progressive eye diseases caused by damage to the optic nerve, which is usually related to increased intraocular pressure. In 2020, more [...]

Applied deep learning is an area that has been evolving rapidly in recent years and is now ubiquitous within the machine learning and artificial intelligence communities. [...]

The goal of this scoping review using PRISMAScr guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews) is to evalua [...]

An exploration of the current relationship between artificial intelligence and the equitable delivery of healthcare. Discusses capacity to enhance bias, improve equitable [...]