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While the professional version of the Mobile App Rating Scale (MARS) has already been translated, and validated into the Spanish language, its user-centered counterpart has not yet been adapted. Furthermore, no other similar tools exist in the Spanish language. The aim of this paper is to adapt and validate User Version of the MARS (uMARS) into the Spanish language.

Making EHR Data More Available for Research and Public Health (MedMorph) is a Centers for Disease Control and Prevention-led initiative developing and demonstrating a reference architecture (RA) and implementation, including Health Level Seven International Fast Healthcare Interoperability Resources (HL7 FHIR) implementation guides (IGs), describing how to leverage FHIR for aligned research and public health access to clinical data for automated data exchange. MedMorph engaged a technical expert panel of more [...]

Hospital capacity management depends on accurate real-time estimates of hospital-wide discharges. Estimation by a clinician requires an excessively large amount of effort and, even when attempted, accuracy in forecasting next-day patient-level discharge is poor. This study aims to support next-day discharge predictions with machine learning by incorporating electronic health record (EHR) audit log data, a resource that captures EHR users' granular interactions with patients' records by communicating various semantics and [...]

In many cases, genetic testing labs provide their test reports as portable document format files or scanned images, which limits the availability of the contained information to advanced informatics solutions, such as automated clinical decision support systems. One of the promising standards that aims to address this limitation is Health Level Seven International (HL7) Fast Healthcare Interoperability Resources Clinical Genomics Implementation Guide-Release 1 (FHIR CG IG STU1). This study aims [...]

This case study illustrates the use of natural language processing for identifying administrative task categories, prevalence, and shifts necessitated by a major event (the COVID-19 [coronavirus disease 2019] pandemic) from user-generated data stored as free text in a task management system for a multisite mental health practice with 40 clinicians and 13 administrative staff members.

We address a first step toward using social media data to supplement current efforts in monitoring population-level medication nonadherence: detecting changes to medication treatment. Medication treatment changes, like changes to dosage or to frequency of intake, that are not overseen by physicians are, by that, nonadherence to medication. Despite the consequences, including worsening health conditions or death, 50% of patients are estimated to not take medications as indicated. Current methods [...]

Injured extremities commonly need to be immobilized by casts to allow proper healing. We propose a method to suppress cast superimpositions in pediatric wrist radiographs based on the cycle generative adversarial network (CycleGAN) model. We retrospectively reviewed unpaired pediatric wrist radiographs (n = 9672) and sampled them into 2 equal groups, with and without cast. The test subset consisted of 718 radiographs with cast. We evaluated different quadratic input sizes (256, 512 [...]

To examine the effectiveness of event notification service (ENS) alerts on health care delivery processes and outcomes for older adults.

Deep significance clustering (DICE) is a self-supervised learning framework. DICE identifies clinically similar and risk-stratified subgroups that neither unsupervised clustering algorithms nor supervised risk prediction algorithms alone are guaranteed to generate.