CancerBERT: a cancer domain-specific language model for extracting breast cancer phenotypes from electronic health records.

ABSTRACT:

Objective

Accurate extraction of breast cancer patients' phenotypes is important for clinical decision support and clinical research. This study developed and evaluated cancer domain pretrained CancerBERT models for extracting breast cancer phenotypes from clinical texts. We also investigated the effect of customized cancer-related vocabulary on the performance of CancerBERT models.

Materials and methods

A cancer-related corpus of breast cancer patients was extracted from the electronic health records of a local hospital. We annotated named entities in 200 pathology reports and 50 clinical notes for 8 cancer phenotypes for fine-tuning and evaluation. We kept pretraining the BlueBERT model on the cancer corpus with expanded vocabularies (using both term frequency-based and ma

SUBMITTER: Zhou S 

PROVIDER: S-EPMC9196678 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature