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Health Text Simplification: An Annotated Corpus for Digestive Cancer Education and Novel Strategies for Reinforcement Learning
April 2, 2024, 7:45 p.m. | Md Mushfiqur Rahman, Mohammad Sabik Irbaz, Kai North, Michelle S. Williams, Marcos Zampieri, Kevin Lybarger
cs.LG updates on arXiv.org arxiv.org
Abstract: Objective: The reading level of health educational materials significantly influences the understandability and accessibility of the information, particularly for minoritized populations. Many patient educational resources surpass the reading level and complexity of widely accepted standards. There is a critical need for high-performing text simplification models in health information to enhance dissemination and literacy. This need is particularly acute in cancer education, where effective prevention and screening education can substantially reduce morbidity and mortality.
Methods: We …
abstract accessibility arxiv cancer complexity cs.ai cs.cl cs.lg education educational health information materials novel patient reading reinforcement reinforcement learning resources standards strategies text the information type
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