Accessibility settings

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

Theme Issue 2025: Artificial Intelligence in Oncology (14) Clinical Information and Decision Making (3582) Natural Language Processing (1242) Electronic Health Records (1674) Machine Learning (3082) Chemotherapy and Side Effects Management (144) Data Science (688) Cancer Prognosis Models and Machine Learning (136) AI applications in genomics and pathology informatics, including generative AI (43)

Published on in Vol 6 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67801, first published .
DeepPhe GitHub page detailing a Natural Language Processing system for cancer phenotype extraction.

Systemic Anticancer Therapy Timelines Extraction From Electronic Medical Records Text: Algorithm Development and Validation

Systemic Anticancer Therapy Timelines Extraction From Electronic Medical Records Text: Algorithm Development and Validation

Authors of this article:

Jiarui Yao1 Author Orcid Image ;   Eli Goldner1 Author Orcid Image ;   Harry Hochheiser2 Author Orcid Image ;   Sean Finan1 Author Orcid Image ;   John Levander2 Author Orcid Image ;   David Harris1 Author Orcid Image ;   Piet C de Groen3 Author Orcid Image ;   Elizabeth Buchbinder4 Author Orcid Image ;   Danielle Bitterman5, 6 Author Orcid Image ;   Jeremy L Warner7, 8 Author Orcid Image ;   Guergana Savova1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. May P, Greß J, Seidel C, Sommer S, Schuler M, Nokodian S, Schröder F, Jung J. Enabling Just-in-Time Clinical Oncology Analysis With Large Language Models: Feasibility and Validation Study Using Unstructured Synthetic Data. JMIR Medical Informatics 2025;13:e78332 View
  2. Li X, Jia B, Liu Y. Tumor Event Extraction based on Semantic Features and Its Application in Auxiliary Diagnosis and Treatment. Journal of Big Data and Computing 2026;4(2):65 View