薬の情報抽出は,ローカルな大型言語モデルを用いて行われます

Phillip Richter-Pechanski1, Marvin Seiferling2, Christina Kiriakou3

  • 1Section of Bioinformatics and Systems Cardiology, Klaus Tschira Institute for Integrative Computational Cardiology, Im Neuenheimer Feld 669, 69120 Heidelberg, DE, Germany; Department of Internal Medicine III, University Hospital, Im Neuenheimer Feld 410, 69120 Heidelberg, DE, Germany; German Center for Cardiovascular Research (DZHK) - Partner site Heidelberg/Mannheim, Im Neuenheimer Feld 669, 69120 Heidelberg, DE, Germany; Informatics for Life, Im Neuenheimer Feld 669, 69120 Heidelberg, DE, Germany; Department of Computational Linguistics, Heidelberg University, Im Neuenheimer Feld 325, 69120 Heidelberg, DE, Germany.

PubMed
まとめ

精密調整されたローカル・ラッグ・ランゲージ・モデル (LLM) は,臨床テキストから最先端の薬物抽出を実現し,正確性と透明性を向上させます. これらのモデルは現実の医療環境で 効率的で信頼性の高いソリューションを提供します

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