NLM DIR Seminar Schedule
UPCOMING SEMINARS
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July 3, 2025 Matthew Diller
Using Ontologies to Make Knowledge Computable -
July 15, 2025 Noam Rotenberg
Cell phenotypes in the biomedical literature: a systematic analysis and the NLM CellLink text mining corpus
RECENT SEMINARS
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July 3, 2025 Matthew Diller
Using Ontologies to Make Knowledge Computable -
July 1, 2025 Yoshitaka Inoue
Graph-Aware Interpretable Drug Response Prediction and LLM-Driven Multi-Agent Drug-Target Interaction Prediction -
June 10, 2025 Aleksandra Foerster
Interactions at pre-bonding distances and bond formation for open p-shell atoms: a step toward biomolecular interaction modeling using electrostatics -
June 3, 2025 MG Hirsch
Interactions among subclones and immunity controls melanoma progression -
May 29, 2025 Harutyun Sahakyan
In silico evolution of globular protein folds from random sequences
Scheduled Seminars on Dec. 5, 2023
Contact NLMDIRSeminarScheduling@mail.nih.gov with questions about this seminar.
Abstract:
Clinical notes can provide insight into caregiver attitudes and how they impact patient care and satisfaction. However, detecting clinician attitudes from the language used in clinical notes is a challenging task, given the concise and standardized format of clinical notes and other contextual factors. In this study, we leverage multiple large language models to identify clinician attitudes from the linguistic features in clinical notes. This approach promises to provide a reliable means of improving patient care, clinician well-being, and communication by identifying specific clinicians' attitude trajectories from clinical notes.