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Ascle: A Python Natural Language Processing Toolkit for Medical Text Generation

2023-11-28 · Rui Yang, Qingcheng Zeng, Keen You, Yujie Qiao, Lucas Huang, Chia-Chun Hsieh, Benjamin Rosand, Jeremy Goldwasser, Amisha D Dave, Tiarnan D. L. Keenan, Emily Y Chew, Dragomir Radev, Zhiyong Lu, Hua Xu, Qingyu Chen, Irene Li

This study introduces Ascle, a pioneering natural language processing (NLP) toolkit designed for medical text generation. Ascle is tailored for biomedical researchers and healthcare professionals with an easy-to-use, all-in-one solution that requires minimal programming expertise. For the first time, Ascle evaluates and provides interfaces for the latest pre-trained language models, encompassing four advanced and challenging generative functions: question-answering, text summarization, text simplification, and machine translation. In addition, Ascle integrates 12 essential NLP functions, along with query and search capabilities for clinical databases. The toolkit, its models, and associated data are publicly available via https://github.com/Yale-LILY/MedGen.

📄 PDF Abstract BibTeX arXiv:2311.16588

Code (3)

yale-lily/ascle 공식 구현

yale-lily/medgen 공식 구현

yale-lily/ehrkit-2022

Tasks

Machine Translation Question AnsweringSentence segmentationText Generation Text Simplification Text Summarization Translation

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