Explore JAMA Network Open’s Health Informatics collection, including open access science about electronic health records, approaches to Big Data, and more.
This cohort study evaluates the association of physician productivity and electronic health record (EHR) use patterns with physician turnover.
This cross-sectional study compares patient electronic health record (EHR) inbox message volume in an ambulatory practice network in New England during the COVID-19 pandemic with prepandemic levels.
This diagnostic and prognostic study describes the development and evaluation of clinical algorithms to predict COVID-19 diagnosis and hospitalization using patient data by citizen scientists, provides an assessment of model performance, and benchmarks model performance on subgroups.
This quality improvement study discusses the development and validation of a fully automated deep learning model to predict surgical complexity and postoperative outcomes in patients undergoing abdominal wall reconstruction based only on preoperative computed tomography imaging.
This review summarizes the use of deep learning models for diagnosis, prognosis, and metastasis detection for oral squamous cell carcinoma by analyzing information from pathological and radiographic images.
This cohort study assesses patient adherence to diabetes screening using hemoglobin A1c level at in-person vs telemedicine encounters during the COVID-19 pandemic in the US.
This cohort study evaluates the feasibility of using noninvasive, wrist-worn wearable devices to detect presymptomatic viral infection after exposure and predict infection severity in patients exposed to H1N1 influenza or human rhinovirus.
This cross-sectional study compares the prevalence of third-party data tracking on websites of the largest and top-rated nonprofit and for-profit hospitals in the US.
This nonrandomized controlled trial evaluated the association of publicly reported feedback for hospital medication safety with improvement in the subsequent year.
This Viewpoint describes benefits and harms of using machine learning algorithms with regard to diagnostic errors, race and ethnicity, and health disparities in the US.
This article summarizes automating technical skills assessment in robotic surgery using deep learning.
This diagnostic/prognostic study evaluates a parsimonious model with a small number of predictors that could feasibly be administered in emergency departments to predict posttraumatic stress disorder or major depression episode 3 months after a motor vehicle collision.
This Viewpoint considers ethical issues intraoperative artificial intelligence (AI) decision support raises for both physicians and patients.
This diagnostic study evaluates a deep learning model for whole-volume segmentation of 4 clinically important pathological features as well as clinical applicability.
This cohort study examines the performance of an interpretable machine learning triage tool in estimating mortality in individuals admitted to the hospital from the emergency department.
This Viewpoint discusses benefits of online data collection while minimizing attendant risks.
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