BioBERT

Researchers introduced Distilled Rapid Embedding Transfer (DRET), a parameter-efficient method that transfers biomedical knowledge from large models like BioBERT and ClinicalBERT into the 66M-paramete…

Researchers at the SMM4H-HeaRD 2026 conference used deep learning models to predict cancer stages from pathology reports, with LightGBM and TF-IDF achieving high AUROC scores. However, performance dro…

AI is being deployed in production healthcare systems to read radiology scans, flag high-risk patients, and automate administrative tasks. Convolutional neural networks match radiologist performance o…

A comparative study of classification models within the InferBERT framework for pharmacovigilance found that domain-specific pre-trained BioBERT outperformed larger models like Med-LLaMA in detecting …