Autonomous artificial intelligence (AI) promises to increase healthcare productivity, but real-
world evidence is lacking. We developed a clinic productivity model to generate testable …

This perspective highlights the importance of addressing social determinants of health
(SDOH) in patient health outcomes and health inequity, a global problem exacerbated by …

The use of data-driven technologies such as Artificial Intelligence (AI) and Machine Learning
(ML) is growing in healthcare. However, the proliferation of healthcare AI tools has outpaced …

Ophthalmology is undergoing a revolutionary change in research, clinical practice, and
surgical interventions. Ophthalmic AI-enabled robotics and chatbot technologies based on …

Diabetic retinopathy can be prevented with screening and early detection. We hypothesized
that autonomous artificial intelligence (AI) diabetic eye exams at the point-of-care would …

The integration of artificial intelligence (AI) into health care offers the potential to enhance
patient care, improve diagnostic precision, and broaden access to health-care services …

Importance Emergency department (ED) visits by older adults with life-limiting illnesses are
a critical opportunity to establish patient care end-of-life preferences, but little is known about …

Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD) pose significant
burdens on individuals and society, necessitating accurate prediction methods. Machine …

Sustainable reimbursement is key for medical artificial intelligence (AI) to benefit patients
and populations at scale; however, achieving reimbursement is complex and requires the …

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 …