Ontology highlight
ABSTRACT: Background
Millions of people affected with complex medical conditions with diverse symptoms often turn to online discourse to share their experiences. While some studies have explored natural language processing methods and medical information extraction tools, these typically focus on generic symptoms in clinical notes and struggle to identify patient-reported, disease-specific, subtle symptoms from online health discourse.Objective
We aimed to extract patient-reported, disease-specific symptoms shared on social media reflecting the lived experiences of thousands of affected individuals and explore the characteristics, prevalence, and occurrence patterns of the symptoms.Methods
We propose a lexicon-based symptom extraction (LSE) method to identify a diverse list o
SUBMITTER: Hossain B
PROVIDER: S-EPMC12475878 | biostudies-literature | 2025 Sep
REPOSITORIES: biostudies-literature