Deep learning models trained on a novel microbiome-specific corpus achieved 96% F1-score for NER and 91% accuracy for entity linking, significantly outperforming traditional pipelines.
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Topic Modeling
Moving in Bioinformatics, medRxiv.
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A ReAct agentic AI system achieves 93.4% accuracy in natural language querying and analysis of TCGA clinical data, surpassing rule-based and LLM baselines.
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- Open access
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The Multimodal Anonymizer achieves near-complete deidentification of multimodal hospital data with over 98% sensitivity and preserves critical clinical information at rates above 99%.
- Open access
A ReAct agentic AI system achieves 93.4% accuracy in natural language querying and analysis of TCGA clinical data, surpassing rule-based and LLM baselines.
- 1 opens in JClub
- Open access
Large language models can serve as human proxies in various scientific and applied contexts, each role requiring distinct validity criteria.
Larger transformer-based language models more accurately predict neural activity, with performance peaking in earlier layers as model size increases, across brain regions.
- Open access
Novel document-level uncertainty aggregation strategies significantly improve active learning performance in ontology curation, with KPSum showing consistent gains over random sampling.
- Open access
- 1 cites
CIViC-Fact reveals that less than 30% of cancer variant claims can be fully validated from abstracts alone, emphasizing the need for full-text evaluation in biomedical verification.
- Open access
- 2 cites
Biomni, a versatile AI agent, autonomously performs diverse biomedical research tasks with high accuracy across 25 domains, accelerating discovery processes.
- 16 cites
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