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Large Language Models for Extraction of Structured Data in Pathology

descriptionPublicationkeyboard_double_arrow_right Report , Other literature type 04 Sep 2024Embargo end date: 09 Sep 2024 English Publisher:Zenodo
Authors: Grothey, Bastian; Tolkach, Yuri;

doi: 10.5281/zenodo.13738209 , 10.5281/zenodo.13685449 , 10.5281/zenodo.13685448 , 10.5281/zenodo.14175293

Large Language Models for Extraction of Structured Data in Pathology

Abstract

This repository contains a comprehensive suite of scripts designed to extract, process, analyze, and visualize structured data from pathology reports. The workflow utilizes various models and APIs, including OpenAI's GPT-4, Hugging Face's LLaMA models, and 4-bit quantized model versions provided by Ollama. Additionally, R scripts are provided for detailed statistical analysis and visualization of the extracted data.

Related Organizations
Keywords

Natural language processing, Pathology, Large language models

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 1
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green
Related to Research communities
Digital Humanities and Cultural Heritage