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M. Carrithers

3 papers hereh-index 162.2k citations54 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.AI1

identity via Semantic Scholar / OpenAlex

most citedA Large Language Model Outperforms Other Computational Approaches to the High-Throughput Phenotyping of Physician Notes

1 citations · 1 across the 2 of their papers we have counts for

collaborators
Showing cs.CLShow all

3 papers · 1 filter

cs.CL2024

Efficient Standardization of Clinical Notes using Large Language Models

Daniel B. Hier, Michael D. Carrithers, Thanh Son Do +1

Clinician notes are a rich source of patient information but often contain inconsistencies due to varied writing styles, colloquialisms, abbreviations, medical jargon, grammatical…

cs.CL2024

High-Throughput Phenotyping of Clinical Text Using Large Language Models

Daniel B. Hier, S. Ilyas Munzir, Anne Stahlfeld +2

High-throughput phenotyping automates the mapping of patient signs to standardized ontology concepts and is essential for precision medicine. This study evaluates the automation of…

cs.CL2024

High Throughput Phenotyping of Physician Notes with Large Language and Hybrid NLP Models

Syed I. Munzir, Daniel B. Hier, Michael D. Carrithers

Deep phenotyping is the detailed description of patient signs and symptoms using concepts from an ontology. The deep phenotyping of the numerous physician notes in electronic healt…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.