A novel medical large language model family with 13/70B parameters, which have SOTA performances on various medical tasks
Cross-type Biomedical Named Entity Recognition with Deep Multi-task Learning (Bioinformatics'19)
Bioformer: an efficient BERT model for biomedical text mining
[EMNLP 2024] This is the code for our paper "BMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers".
This repository contains the code used for distillation and fine-tuning of compact biomedical transformers that have been introduced in the paper "On The Effectiveness of Compact Biomedical Transformers"
Graph-based RAG system for biomedical nutrigenetic knowledge discovery. Enables natural language queries on gene-nutrient interactions, supports personalized nutrition counseling, and runs 100% locally with Ollama LLMs and SBERT embeddings.
Systematic evaluation of hallucination risks in Large Language Models (GPT-4, Claude 3, Gemini Pro) for clinical proteomics and mass spectrometry interpretation. Production-ready detection framework with comprehensive benchmarks.
BERT-for-BioNLP-OST2019-AGAC-Task2
AGAC-BioNL-OST2009-Task1 BERT+CRF
MSR Cambridge Internship Summer 2023
Cancer-Alterome is a comprehensive and curated dataset that focuses on the investigation of regulatory events caused by gene alteration in the context of cancer.
Implements relation extraction for biomedical texts using Hard Negative Mining to improve accuracy in identifying complex entity relationships. Includes code for data processing, training, and evaluation with BioC-format datasets.
Fine-tune with TEA
PheSeq, A Bayesian Deep Learning Model to Enhance and Interpret the Gene Disease Association Studies
About Cross-type Biomedical Named Entity Recognition with Deep Multi-task Learning
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