Prospective Evaluation of Large Language Model Integration Into a Classical Hematology Case Conference
Tariq Kewan, Alfred I Lee, Layla Van Doren

TL;DR
Using large language models in hematology case discussions was found to be practical and beneficial for education and diagnosis.
Contribution
Demonstrated the feasibility and value of integrating large language models into clinical hematology conferences.
Findings
Integration of large language models into hematology conferences was feasible.
Clinicians found the tool diagnostically and educationally valuable.
The tool increased clinician familiarity and interest in AI applications.
Abstract
Prospective integration of large language model tools into a classical hematology challenging-cases conference was feasible, increased clinician familiarity and interest, and was perceived as diagnostically and educationally valuable.
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Taxonomy
TopicsArtificial Intelligence in Healthcare and Education · Machine Learning in Healthcare · Explainable Artificial Intelligence (XAI)
