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To improve performance of medical entity normalization across many languages, especially when fewer language resources are available compared to English.

There is no guidance to support the reporting of systematic reviews of mobile health (mhealth) apps (app reviews), so authors attempt to use/modify the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). There is a need for reporting guidance, building on PRISMA where appropriate, tailored to app reviews. The objectives were to describe the reporting quality of published mHealth app reviews, identify the need for, and develop potential candidate [...]

The National Library of Medicine (NLM) currently indexes close to a million articles each year pertaining to more than 5300 medicine and life sciences journals. Of these, a significant number of articles contain critical information about the structure, genetics, and function of genes and proteins in normal and disease states. These articles are identified by the NLM curators, and a manual link is created between these articles and the corresponding [...]

In the general hospital wards, machine learning (ML)-based early warning systems (EWSs) can identify patients at risk of deterioration to facilitate rescue interventions. We assess subpopulation performance of a ML-based EWS on medical and surgical adult patients admitted to general hospital wards.

The resurgence of syphilis in the United States presents a significant public health challenge. Much of the information needed for syphilis surveillance resides in electronic health records (EHRs). In this manuscript, we describe a surveillance platform for automating the extraction of EHR data, known as SmartChart Suite, and the results from a pilot.

Statistical and artificial intelligence algorithms are increasingly being developed for use in healthcare. These algorithms may reflect biases that magnify disparities in clinical care, and there is a growing need for understanding how algorithmic biases can be mitigated in pursuit of algorithmic fairness. We conducted a scoping review on algorithmic individual fairness (IF) to understand the current state of research in the metrics and methods developed to achieve IF and [...]

This study aims to investigate whether different types of electronic health record (EHR) users have distinct preferences for data quality assessment indicators (DQAI) and explore how these preferences can guide the enhancement of EHR systems and the optimization of related policies.

As artificial intelligence evolves, integrating speech processing into home healthcare (HHC) workflows is increasingly feasible. Audio-recorded communications enhance risk identification models, with automatic speech recognition (ASR) systems as a key component. This study evaluates the transcription accuracy and equity of 4 ASR systems-Amazon Web Services (AWS) General, AWS Medical, Whisper, and Wave2Vec-in transcribing patient-nurse communication in US HHC, focusing on their ability in accurate transcription of speech from Black and [...]

To explore implementing regular expressions (RegEx) to streamline patient identification and classification for matching to clinical trials.

To describe the diagnostic characteristics of the proprietary Epic sepsis predictive model best practice advisory (BPA) alert for physicians in the emergency department (ED).