ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2022
PathologyBERT - Pre-trained Vs. A New Transformer Language Model for Pathology Domain.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed.
- Natural Language Processing Methods Automate Molecular Marker Extraction From Glioma Pathology Reports.Neurosurgery · 2026Article
- Leveraging sequence-to-sequence models for semantic annotation of Dutch pathology reports.Journal of pathology informatics · 2026Article
- Multimodal Data Fusion for Whole-Slide Histopathology Image Classification.Journal of healthcare informatics research · 2025Article
- Enhancing Adverse Event Reporting With Clinical Language Models: Inpatient Falls.Journal of advanced nursing · 2025Observational
- Using large language models for clinical staging of colorectal cancer from imaging reports: a pilot study.Annals of surgical treatment and research · 2025Article
- DrugBERT: a BERT-based approach integrating LDA topic embedding and efficacy-aware mechanism for predicting anti-tumor drug efficacy.Journal of translational medicine · 2025Article
- Development and evaluation of large-language models (LLMs) for oncology: A scoping review.PLOS digital health · 2025Article
- MISTIC: a novel approach for metastasis classification in Italian electronic health records using transformers.BMC medical informatics and decision making · 2025Article
- Large language models in cancer: potentials, risks, and safeguards.BJR artificial intelligence · 2025Review
- Task-Specific Transformer-Based Language Models in Health Care: Scoping Review.JMIR medical informatics · 2024Article
- Large language model to multimodal large language model: A journey to shape the biological macromolecules to biological sciences and medicine.Molecular therapy. Nucleic acids · 2024Review
- Applications of Large Language Models in Pathology.Bioengineering (Basel, Switzerland) · 2024Review
- Crowdsourcing with Enhanced Data Quality Assurance: An Efficient Approach to Mitigate Resource Scarcity Challenges in Training Large Language Models for Healthcare.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Local Large Language Models for Complex Structured Tasks.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Quilt-1M: One Million Image-Text Pairs for Histopathology.Advances in neural information processing systems · 2023Article
- Embracing Large Language Models for Medical Applications: Opportunities and Challenges.Cureus · 2023Article
- Spatially Aware Transformer Networks for Contextual Prediction of Diabetic Nephropathy Progression from Whole Slide Images.medRxiv : the preprint server for health sciences · 2023Article
- Spatially Aware Transformer Networks for Contextual Prediction of Diabetic Nephropathy Progression from Whole Slide Images.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Development of an interactive web dashboard to facilitate the reexamination of pathology reports for instances of underbilling of CPT codes.Journal of pathology informatics · 2023Article
- Organizational preparedness for the use of large language models in pathology informatics.Journal of pathology informatics · 2023Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pathology text mining is a challenging task given the reporting variability and constant new findings in cancer sub-type definitions. However, successful text mining of a large pathology database can play a critical role to advance 'big data' cancer research like similarity-based treatment selection, case identification, prognostication, surveillance, clinical trial screening, risk stratification, and many others. While there is a growing interest in developing language models for more specific clinical domains, no pathology-specific language space exist to support the rapid data-mining development in pathology space. In literature, a few approaches fine-tuned general transformer models on specialized corpora while maintaining the original tokenizer, but in fields requiring specialized terminology, these models often fail to perform adequately. We propose PathologyBERT - a pre-trained masked language model which was trained on 347,173 histopathology specimen reports and publicly released in the Huggingface
Indexed as
Identifiers
37128387PMC10148354What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.