Clinical BERT

Clinical BERT, a type of natural language processing model, aims to improve the analysis of clinical text data by leveraging the power of pre-trained language models like BERT. Current research focuses on adapting these models to handle longer clinical notes, evaluating their performance across diverse clinical domains and tasks (e.g., phenotype recognition, trial eligibility classification, sentiment analysis), and mitigating biases present in training data. These advancements hold significant promise for automating clinical tasks, improving diagnostic accuracy, and facilitating more efficient healthcare delivery.

Papers

February 26, 2024

Adaptation of Biomedical and Clinical Pretrained Models to French Long Documents: A Comparative Study
Adrien Bazoge, Emmanuel Morin, Beatrice Daille, Pierre-Antoine Gourraud
Language Model Comparative Study Adaptation Concern Sequence Model Biomedical Research Clinical BERT French Biomedical

November 15, 2023

An Eye on Clinical BERT: Investigating Language Model Generalization for Diabetic Eye Disease Phenotyping
Keith Harrigian, Tina Tang, Anthony Gonzales, Cindy X. Cai, Mark Dredze
Diabetic Retinopathy Clinical Data Human Eye Clinical NLP Task Clinical BERT Language Model Generalization

September 14, 2023

Text Classification of Cancer Clinical Trial Eligibility Criteria
Yumeng Yang, Soumya Jayaraj, Ethan B Ludmir, Kirk Roberts
Natural Language Text Classification Clinical BERT Eligibility Criterion Clinical Trial Eligibility Criterion

August 11, 2023

Enhancing Phenotype Recognition in Clinical Notes Using Large Language Models: PhenoBCBERT and PhenoGPT
Jingye Yang, Cong Liu, Wendy Deng, Da Wu, Chunhua Weng, Yunyun Zhou, Kai Wang
BERT Model Clinical Note Phenotype Recognition Po Tagging Continuous Valued Phenotype Clinical BERT

August 2, 2023

Bio+Clinical BERT, BERT Base, and CNN Performance Comparison for Predicting Drug-Review Satisfaction
Yue Ling
Natural Language Processing Domain Specific CNN Performance Clinical BERT Drug Review

August 19, 2022

Graph-Augmented Cyclic Learning Framework for Similarity Estimation of Medical Clinical Notes
Can Zheng, Yanshan Wang, Xiaowei Jia
Clinical Note Clinical Text Semantic Textual Similarity Cyclic Learning Clinical BERT

August 9, 2022

A Multimodal Transformer: Fusing Clinical Notes with Structured EHR Data for Interpretable In-Hospital Mortality Prediction
Weimin Lyu, Xinyu Dong, Rachel Wong, Songzhu Zheng, Kayley Abell-Hart, Fusheng Wang, Chao Chen
Clinical Note Multimodal Transformer Clinical Narrative Hospital Mortality Prediction Clinical BERT

August 2, 2022

Gender bias in (non)-contextual clinical word embeddings for stereotypical medical categories
Gizem Sogancioglu, Fabian Mijsters, Amar van Uden, Jelle Peperzak
Jina Embeddings Word Embeddings Gender Bias Stereotype Content BioNLP Workshop Clinical BERT

Clinical BERT

Papers

Adaptation of Biomedical and Clinical Pretrained Models to French Long Documents: A Comparative Study

An Eye on Clinical BERT: Investigating Language Model Generalization for Diabetic Eye Disease Phenotyping

Text Classification of Cancer Clinical Trial Eligibility Criteria

Enhancing Phenotype Recognition in Clinical Notes Using Large Language Models: PhenoBCBERT and PhenoGPT

Bio+Clinical BERT, BERT Base, and CNN Performance Comparison for Predicting Drug-Review Satisfaction

Graph-Augmented Cyclic Learning Framework for Similarity Estimation of Medical Clinical Notes

A Multimodal Transformer: Fusing Clinical Notes with Structured EHR Data for Interpretable In-Hospital Mortality Prediction

Gender bias in (non)-contextual clinical word embeddings for stereotypical medical categories