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Although there exists a variety of anonymous survey software, this study aimed to develop an improved system that incentivizes responses and proactively detects fraud attempts while maintaining anonymity.

Given widespread excitement around predictive analytics and the proliferation of machine learning algorithms that predict outcomes, a key next step is understanding how this information is-or should be-communicated with patients.

To develop an online crowdsourcing platform where oncologists and other survivorship experts can adjudicate risk for complications in follow-up.

The objective of this study was to determine the feasibility of a computerized clinical decision support (cCDS) tool to facilitate referral to adult healthcare services for children with special healthcare needs. A transition-specific cCDS was implemented as part of standard care in a general pediatrics clinic at a tertiary care academic medical center. The cCDS alerts providers to patients 17-26 years old with 1 or more of 15 diagnoses that may [...]

The objective of this study is to develop a deep learning pipeline to detect signals on dietary supplement-related adverse events (DS AEs) from Twitter.

Attention networks learn an intelligent weighted averaging mechanism over a series of entities, providing increases to both performance and interpretability. In this article, we propose a novel time-aware transformer-based network and compare it to another leading model with similar characteristics. We also decompose model performance along several critical axes and examine which features contribute most to our model's performance.

A growing research literature has highlighted the work of managing and triaging clinical messages as a major contributor to professional exhaustion and burnout. The goal of this study was to discover and quantify the distribution of message content sent among care team members treating patients with breast cancer.

Provider burnout is a crisis in healthcare and leads to medical errors, a decrease in patient satisfaction, and provider turnover. Many feel that the increased use of electronic health records contributes to the rate of burnout. To avoid provider burnout, many organizations are hiring medical scribes. The goal of this study was to identify relevant elements of the provider-scribe relationship (like decreasing documentation burden, extending providers' careers, and preventing retirement) [...]

Genomic data are prevalent, leading to frequent encounters with uninterpreted variants or mutations with unknown mechanisms of effect. Researchers must manually aggregate data from multiple sources and across related proteins, mentally translating effects between the genome and proteome, to attempt to understand mechanisms.

The emergence of COVID-19 resulted in postponement of nonemergent surgical procedures for cardiac patients in London. mHealth represented a potentially viable mechanism for highlighting deteriorating patients on the lengthened cardiac surgical waiting lists.