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 The Accreditation Council for Graduate Medical Education suggests that Clinical Informatics (CI) fellowship programs foster broad skills, which include collaboration and project management. However, they do not dictate how to best accomplish these learning objectives.

 Variability in cardiopulmonary arrest training and management leads to inconsistent outcomes during in-hospital cardiac arrest. Existing clinical decision aids, such as American Heart Association (AHA) advanced cardiovascular life support (ACLS) pocket cards and third-party mobile apps, often lack comprehensive management guidance. We developed a novel, guided ACLS mobile app and evaluated user performance during simulated cardiac arrest according to the 2020 AHA ACLS guidelines via randomized controlled trial.

 Imaging and Clinical Informatics are domains of biomedical informatics. Imaging Informatics topics are often not covered in depth in most Clinical Informatics fellowships. While dedicated Imaging Informatics fellowships exist, they may not have the same rigor as ACGME (Accreditation Council for Graduate Medical Education) accredited Clinical Informatics fellowships and they do not provide a direct path toward subspecialty board certification.

This study aims to investigate the feasibility of using Large Language Models (LLMs) to engage with patients at the time they are drafting a question to their healthcare providers, and generate pertinent follow-up questions that the patient can answer before sending their message, with the goal of ensuring that their healthcare provider receives all the information they need to safely and accurately answer the patient's question, eliminating back-and-forth messaging, and [...]

 The use of medical mobile applications (apps) to enhance learning is widespread in medical education. Despite the large number of medical apps used among medical students for learning, many apps have not been evaluated using validated instruments. Finding relevant and valuable apps for student learning might be difficult.

 The overall goal of this work is to create a patient-reported outcome (PRO) and decision support system to help postpartum patients determine when to seek care for concerning symptoms. In this case study, we assessed differences in perspectives for application design needs based on race, ethnicity, and preferred language.

To explore the feasibility of validating Dutch concept extraction tools using annotated corpora translated from English, focusing on preserving annotations during translation and addressing the scarcity of non-English annotated clinical corpora.

The integration of these preventive guidelines with Electronic Health Records (EHRs) systems, coupled with the generation of personalized preventive care recommendations, holds significant potential for improving healthcare outcomes. Our study investigates the feasibility of using Large Language Models (LLMs) to automate the assessment criteria and risk factors from the guidelines for future analysis against medical records in EHR.

 This study aimed to evaluate implementation of a digital remote symptom monitoring intervention that delivered weekly symptom questionnaires and included the option to receive nurse callbacks via a mobile app for asthma patients in primary care.

 This study aimed to pilot an application-based patient diagnostic questionnaire (PDQ) and assess the concordance of the admission diagnosis reported by the patient and entered by the clinician.