Ascle: A Python Natural Language Processing Toolkit for Medical Text Generation
It addresses the need for accessible tools in medical text generation for biomedical and healthcare domains, but is incremental as it packages existing methods into a toolkit.
The study introduces Ascle, a Python NLP toolkit for medical text generation, providing an easy-to-use solution for biomedical researchers and healthcare professionals with interfaces for pre-trained models and 12 essential functions.
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.