Explore JAMA Network Open’s Health Informatics collection, including open access science about electronic health records, approaches to Big Data, and more.
This consensus statement consolidates the limited existing literature with expert opinion to create a checklist to guide developers and reviewers of dermatology artificial intelligence.
This article explains methods for computational psychiatry to study hallucinations in humans and murine models.
This cohort study investigates the association between sickle cell trait and risk of stillbirth in pregnant people.
This survey study assesses the attitudes and perceptions of multidisciplinary cancer care clinicians (from the fields of medical oncology, radiation oncology, surgical oncology, survivorship, and oncology navigation) toward telehealth and secure messages.
This cohort study uses rule-based natural language processing algorithms applied to electronic health record data to examine the overall burden of and temporal trends in the rate of hospitalizations for worsening heart failure overall and by the degree of systolic dysfunction.
This descriptive study evaluates the association between nursing reports of sepsis overalerting and alert volume by quantifying the number of alerts generated by the Epic Sepsis Model at 24 US hospitals before and during the COVID-19 pandemic.
This diagnostic study assesses the ability of a deep learning model to detect evidence of cognitive decline before a diagnosis of mild cognitive impairment using clinical notes from electronic health records.
This diagnostic study evaluates the accuracy and assessment time of an artificial intelligence (AI)–augmented digital system compared with standard microscopic assessment for interpretation of slides with colorectal polyp samples.
This comparative effectiveness study uses data from a multiple sclerosis registry and linked electronic health records to compare the relapse outcomes between 2 disease-modifying treatment pairs: dimethyl fumarate vs fingolimod and natalizumab vs rituximab.
This diagnostic study compares the accuracy of an automated diabetic retinopathy detection system with the Early Treatment Diabetic Retinopathy Study reference standard in adults with diabetic retinopathy.
This cross-sectional study performs deep phenotyping and identification of severity-associated factors in adolescent and adult patients with atopic dermatitis.
This cross-sectional study investigates the association of undertriage to hospital wards after surgical procedures with mortality, morbidity, and resource use.
This quality improvement study evaluates patient and clinician factors to assess which factors are associated with the successful completion or failure of telemedicine video appointments.
This diagnostic study examines the ability of an artificial intelligence–powered platform vs manual evaluation to accurately and efficiently detect, grade, and quantify prostate cancer and reduce interobserver variability among experienced pathologists.
This scoping review analyzes the literature on algorithms assessing skin disease for data set criteria, emphasizing transparency and concerns about bias.
This Viewpoint discusses benefits of online data collection while minimizing attendant risks.
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 a major depression episode 3 months after a motor vehicle collision.
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