Ontology highlight
ABSTRACT:
SUBMITTER: Nishioka S
PROVIDER: S-EPMC10509234 | biostudies-literature | 2023 Sep
REPOSITORIES: biostudies-literature
Nishioka Satoshi S Asano Masaki M Yada Shuntaro S Aramaki Eiji E Yajima Hiroshi H Yanagisawa Yuki Y Sayama Kyoko K Kizaki Hayato H Hori Satoko S
Scientific reports 20230919 1
Adverse event (AE) management is important to improve anti-cancer treatment outcomes, but it is known that some AE signals can be missed during clinical visits. In particular, AEs that affect patients' activities of daily living (ADL) need careful monitoring as they may require immediate medical intervention. This study aimed to build deep-learning (DL) models for extracting signals of AEs limiting ADL from patients' narratives. The data source was blog posts written in Japanese by breast cancer ...[more]