Importance: Limited qualitative studies exist evaluating ambient artificial intelligence (AI) scribe tools. Such studies can provide deeper insights into ambient AI implementations by capturing lived experiences.
Objective: To evaluate physician perspectives on ambient AI scribes.
Alzheimer's disease (AD) is characterized by progressive cognitive decline, severe brain atrophy and neuroinflammation. We conducted a randomized, double-blind, placebo-controlled, parallel-group phase 2a clinical trial that tested the safety and efficacy of laromestrocel, a bone-marrow-derived, allogeneic mesenchymal stem-cell therapy, in slowing AD clinical progression, atrophy and neuroinflammation. Participants across ten centers in the United States were randomly assigned 1:1:1:1 to four infusion groups: group 1 (placebo; four monthly infusions, n = 12); group 2 (25 million cells, one infusion followed by three monthly infusions of placebo, n = 13); group 3 (25 million cells; four monthly doses, n = 13); and group 4 (100 million cells; four monthly doses, n = 11).
View Article and Find Full Text PDFWith rapidly evolving artificial intelligence solutions, healthcare organizations need an implementation roadmap. A "clinical trials" informed approach can promote safe and impactful implementation of artificial intelligence. This framework includes four phases: (1) Safety; (2) Efficacy; (3) Effectiveness and comparison to an existing standard; and (4) Monitoring.
View Article and Find Full Text PDFBackground: Generative AI, particularly large language models (LLMs), holds great potential for improving patient care and operational efficiency in healthcare. However, the use of LLMs is complicated by regulatory concerns around data security and patient privacy. This study aimed to develop and evaluate a secure infrastructure that allows researchers to safely leverage LLMs in healthcare while ensuring HIPAA compliance and promoting equitable AI.
View Article and Find Full Text PDFThe major histocompatibility complex (MHC) class I-related molecule MHC-class-I-related protein 1 (MR1) presents metabolites to distinct MR1-restricted T cell subsets, including mucosal-associated invariant T (MAIT) and MR1T cells. However, self-reactive MR1T cells and the nature of recognized antigens remain underexplored. Here, we report a cell endogenous carbonyl adduct of adenine (8-(9H-purin-6-yl)-2-oxa-8-azabicyclo[3.
View Article and Find Full Text PDFJ Am Med Inform Assoc
February 2025
Objectives: To quantify utilization and impact on documentation time of a large language model-powered ambient artificial intelligence (AI) scribe.
Materials And Methods: This prospective quality improvement study was conducted at a large academic medical center with 45 physicians from 8 ambulatory disciplines over 3 months. Utilization and documentation times were derived from electronic health record (EHR) use measures.
J Am Med Inform Assoc
February 2025
Objective: This study evaluates the pilot implementation of ambient AI scribe technology to assess physician perspectives on usability and the impact on physician burden and burnout.
Materials And Methods: This prospective quality improvement study was conducted at Stanford Health Care with 48 physicians over a 3-month period. Outcome measures included burden, burnout, usability, and perceived time savings.
Introduction: Influenza causes significant mortality and morbidity in the U.S., yet less than half of adults receive influenza vaccination.
View Article and Find Full Text PDF: There are limited data about left atrial appendage closure (LAAC) in patients with cancer. We therefore sought to compare the outcome after LAAC in patients with vs. without cancer in a multicentre registry.
View Article and Find Full Text PDFImportance: Large language models (LLMs) can assist in various health care activities, but current evaluation approaches may not adequately identify the most useful application areas.
Objective: To summarize existing evaluations of LLMs in health care in terms of 5 components: (1) evaluation data type, (2) health care task, (3) natural language processing (NLP) and natural language understanding (NLU) tasks, (4) dimension of evaluation, and (5) medical specialty.
Data Sources: A systematic search of PubMed and Web of Science was performed for studies published between January 1, 2022, and February 19, 2024.
The increasing interest in leveraging generative AI models in healthcare necessitates secure infrastructure at academic medical centers. Without an all-encompassing secure system, researchers may create their own insecure microprocesses, risking the exposure of protected health information (PHI) to the public internet or its inadvertent incorporation into AI model training. To address these challenges, our institution implemented a secure pathway to the Azure OpenAI Service using our own private OpenAI instance which we fully control to facilitate high-throughput, secure LLM queries.
View Article and Find Full Text PDFCyclic oligoadenylates (cOAs) are small second messenger molecules produced by the type III CRISPR-Cas system as part of the prokaryotic immune response. The role of cOAs is to allosterically activate downstream effector proteins that induce dormancy or cell death, and thus abort viral spread through the population. Interestingly, different type III systems have been reported to utilize different cOA stoichiometries (with 3 to 6 adenylate monophosphates).
View Article and Find Full Text PDFMR1T cells are a recently found class of T cells that recognize antigens presented by the major histocompatibility complex-I-related molecule MR1 in the absence of microbial infection. The nature of the self-antigens that stimulate MR1T cells remains unclear, hampering our understanding of their physiological role and therapeutic potential. By combining genetic, pharmacological, and biochemical approaches, we found that carbonyl stress and changes in nucleobase metabolism in target cells promote MR1T cell activation.
View Article and Find Full Text PDFJAMA Netw Open
March 2024
Importance: The emergence and promise of generative artificial intelligence (AI) represent a turning point for health care. Rigorous evaluation of generative AI deployment in clinical practice is needed to inform strategic decision-making.
Objective: To evaluate the implementation of a large language model used to draft responses to patient messages in the electronic inbox.
Objectives: We aimed to evaluate thrombotic and hemorrhagic complications with heparin versus bivalirudin use in veno-venous extracorporeal membrane oxygenation (V-V ECMO).
Methods: We performed a retrospective cohort study of adult patients placed on V-V ECMO with intravenous anticoagulation with either heparin or bivalirudin. Time to thrombotic event and major bleed were analyzed in addition to related outcomes.
Background: Despite the ubiquitous utilization of central venous catheters in clinical practice, their use commonly provokes thromboembolism. No prophylactic strategy has shown sufficient efficacy to justify routine use. Coagulation factors FXI (factor XI) and FXII (factor XII) represent novel targets for device-associated thrombosis, which may mitigate bleeding risk.
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