This paper is in the following e-collection/theme issue:

Artificial Intelligence (1198) Natural Language Processing (644) Ontologies, Classifications, and Coding (225) Machine Learning (1385) Pathology (8) Innovations in Cancer Diagnostic and Decision Support (50) Clinical Information and Decision Making (1328)

Published on in Vol 24, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27210, first published .
A Question-and-Answer System to Extract Data From Free-Text Oncological Pathology Reports (CancerBERT Network): Development Study

A Question-and-Answer System to Extract Data From Free-Text Oncological Pathology Reports (CancerBERT Network): Development Study

A Question-and-Answer System to Extract Data From Free-Text Oncological Pathology Reports (CancerBERT Network): Development Study

Authors of this article:

Joseph Ross Mitchell1, 2, 3 Author Orcid Image ;   Phillip Szepietowski4 Author Orcid Image ;   Rachel Howard4 Author Orcid Image ;   Phillip Reisman4 Author Orcid Image ;   Jennie D Jones4 Author Orcid Image ;   Patricia Lewis4 Author Orcid Image ;   Brooke L Fridley5 Author Orcid Image ;   Dana E Rollison4 Author Orcid Image
Article Authors Cited by (4) Tweetations (9) Metrics

Journals

  1. Sim J, Huang X, Horan M, Baker J, Huang I. Using natural language processing to analyze unstructured patient-reported outcomes data derived from electronic health records for cancer populations: a systematic review. Expert Review of Pharmacoeconomics & Outcomes Research 2024;24(4):467 View
  2. Yang T, Sucholutsky I, Jen K, Schonlau M. exKidneyBERT: a language model for kidney transplant pathology reports and the crucial role of extended vocabularies. PeerJ Computer Science 2024;10:e1888 View
  3. Cheng J. Applications of Large Language Models in Pathology. Bioengineering 2024;11(4):342 View