Analyzing Cancer Patients' Experiences with Embedding-based Topic Modeling and LLMs 事件

Analyzing Cancer Patients' Experiences with Embedding-based Topic Modeling and LLMs arXiv:2601.12154v2 Announce Type: replace Abstract: This study investigates the use of neural topic modeling and LLMs to uncover meaningful themes from patient storytelling data, to offer insights that could contribute to more patient-oriented healthcare practices. We analyze a collection of transcribed interviews with cancer patients (132,722 words in 13 interviews). We first evaluate BERTopic and Top2Vec for i