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| http://dx.doi.org/10.3389/frai.2023.1203910 | DOI Listing |
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An evaluation framework for clinical use of large language models in patient interaction tasks.
Nat Med
January 2025
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
The integration of large language models (LLMs) into clinical diagnostics has the potential to transform doctor-patient interactions. However, the readiness of these models for real-world clinical application remains inadequately tested. This paper introduces the Conversational Reasoning Assessment Framework for Testing in Medicine (CRAFT-MD) approach for evaluating clinical LLMs.
View Article and Find Full Text PDFConceptual Frameworks in Neurology Education Research.
Neurol Educ
March 2025
Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
This article discusses conceptual frameworks in neurology education research. We provide practical case examples highlighting the conceptual framework development process for different research scenarios in neurology education. We explore the steps that shape the conceptual framework process, including defining the educational problem, exploring the scholarly conversation on the topic of study through understanding the literature and outlining its gaps, constructing research questions, selecting the theoretical frameworks that underpin the study, and choosing the appropriate methodology and methods for the research questions.
View Article and Find Full Text PDFPiecing together the narrative of #longcovid: an unsupervised deep learning of 1,354,889 X (formerly Twitter) posts from 2020 to 2023.
Front Public Health
December 2024
Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Objective: To characterize the public conversations around long COVID, as expressed through X (formerly Twitter) posts from May 2020 to April 2023.
Methods: Using X as the data source, we extracted tweets containing #long-covid, #long_covid, or "long covid," posted from May 2020 to April 2023. We then conducted an unsupervised deep learning analysis using Bidirectional Encoder Representations from Transformers (BERT).
Breaking Bad News to Learners: How Well Does the SPIKES Clinical Model Translate?
Perspect Med Educ
December 2024
University of California, San Francisco, US.
When health professions learners do not meet standards on assessments, educators need to share this information with the learners and determine next steps to improve their performance. Those conversations can be difficult, and educators may lack confidence or skill in holding them. For clinician-educators with experience sharing challenging news with patients, using an analogy from clinical settings may help with these conversations in the education context.
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