Bioinformatics'2020: BioBERT: a pre-trained biomedical language representation model for biomedical text mining

BioBERT: a pre-trained biomedical language representation model for biomedical text mining

PyTorch Implementation of BioBERT

Browse Covid-19 & SARS-CoV-2 Scientific Papers with Transformers 🦠 📖

Pre-trained Language Model for Biomedical Question Answering

BioBert Pytorch

NER and Relation Extraction from Electronic Health Records (EHR).

Biomedical and Clinical BERT for Portuguese Language

Implementation and demo of explainable coding of clinical notes with Hierarchical Label-wise Attention Networks (HLAN)

Token and Sentence level embeddings from BioBERT model

MIL-RBERT: A Data-driven Approach for Noise Reduction in Distantly Supervised Biomedical Relation Extraction (BioNLP @ ACL 2020)

Ready to use BioBert pytorch weights for HuggingFace pytorch BertModel :relieved:

Data and codes for BioBERT-MRC

Relation Extraction using BERT and BioBERT - using BERT, we achieved new state of the art results

BioBERT model fine tuned for NER task on Pubmed Dataset

AI-driven drug repurposing framework integrating knowledge graphs, MolBERT, and BioBERT. Features heteroscedastic uncertainty modeling and Engression-based distributional regression for calibrated, interpretable pIC50 prediction.

We employed pre-trained BERT models (distillBERT, BioBert, and SciBert) for text-classifications of the titles and abstracts of clinical trials in medical psychology. The average score of AUC is 0.92. A stacked model was then built by featuring the probability predicted by distillBERT and keywords of search domains. The AUC improved to 0.96 with F1, precision, and recall increasing to 0.95, 0.94, and 0.96 respectively. Training sample size of 100 results in the most cost-effective performance.

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This project applies Fine-tuning BERT & BioBERT on BC5CDR for biomedical named entity recognition (diseases + chemicals).

Computational Strategies in Nutrigenetics: Constructing a Reference Dataset of Nutrition-Associated Genetic Polymorphisms https://doi.org/10.1101/2023.08.04.23293659

Transfer Learning for Biomedical Relation Extraction Seminar. Applying BioBERT & SciBERT to Relation Extraction (protein-protein-interaction).

🧬 Fine-Tuning Large Language and Protein Models on a single T4 GPU via Distillation, Quantization and Low-Rank Adaptation to run inference on proteins functions.

Variant pathogenicity prediction (XGBoost + SHAP) meets biomedical literature Q&A (RAG + Claude). Built on ClinVar, gnomAD, and BioBERT.

COVID-19 Open Research Dataset Challenge (CORD-19)

Trying to reproduce BioBert

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Extracting DDIs from biomedical documents with BioBERT and Knowledge from Document

pytorch BERT implementation applied on Bio NER

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👑🦠 Annotating PMC and PubMed articles for Covid-related entities