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One of the increasingly accepted methods to evaluate the privacy of synthetic data is by measuring the risk of membership disclosure. This is a measure of the F1 accuracy that an adversary would correctly ascertain that a target individual from the same population as the real data is in the dataset used to train the generative model, and is commonly estimated using a data partitioning methodology with a 0.5 partitioning [...]

Understanding the current state of real-world Fast Healthcare Interoperability Resources (FHIR) applications (apps) will benefit biomedical research and clinical care and facilitate advancement of the standard. This study aimed to provide a preliminary assessment of these apps' clinical, technical, and implementation characteristics.

The purpose of this study is to provide an overview of apps to help control the spread of Covid-19 in Germany and rate them according to standardized instruments.

COVID-19 accelerated telehealth use to ensure care delivery, but there is limited data on the patient perspective. This study aimed to examine telehealth visit uptake before and during COVID-19 and correlates of patient satisfaction and interest in future telehealth visits.

The goal of this study was to investigate the relationship between comorbidities and ethnic health disparities in a diverse, cosmopolitan population.

To examine the association of the coronavirus disease 2019 (COVID-19) pandemic, the association of sex, and the joint association of sex and the COVID-19 pandemic with health communication, physical activity, mental health, and behavioral health.

Given time constraints, poorly organized information, and complex patients, primary care providers (PCPs) can benefit from clinical decision support (CDS) tools that aggregate and synthesize problem-specific patient information. First, this article describes the design and functionality of a CDS tool for chronic noncancer pain in primary care. Second, we report on the retrospective analysis of real-world usage of the tool in the context of a pragmatic trial.

We aim to reduce overfitting and model overconfidence by distilling the knowledge of an ensemble of deep learning models into a single model for the classification of cancer pathology reports.

Simulation is a mainstay of comparative- and cost-effectiveness research when empirical data are not available. The Synthea platform, originally designed for generating realistically coded longitudinal health records for software testing, implements data generation models specified in publicly contributed modules representing patients' life cycle and disease and treatment progression. We test the hypothesis that Synthea can be used for simulation studies that draw parameters from observational studies and randomized trials. We [...]

[This corrects the article DOI: 10.1093/jamiaopen/ooab112.].