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

28 November 2023
Rui Yang
Qingcheng Zeng
Keen You
Yujie Qiao
Lucas Huang
Chia-Chun Hsieh
Benjamin Rosand
Jeremy Goldwasser
Amisha D. Dave
T. Keenan
Emily Y. Chew
Dragomir R. Radev
Zhiyong Lu
Hua Xu
Qingyu Chen
Irene Z Li
    ELM
    LM&MA
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Abstract

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.

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