Year: 2025
Type: article
Abstract: Cyberchondria behavior, characterized by excessive online health searching, has become agrowing concern in the digital age. This behavior can lead to increased health anxiety, decreasedquality of life, and unnecessary healthcare utilization. However, detecting cyberchondria behavioris a challenging task due to the complexity and variability of online behaviors. Traditional machinelearning approaches often rely on hand-crafted features and may not capture the nuanced patternsof cyberchondria behavior. To address this challenge, a novel approach using Deep Q Network(DQN) is proposed to detect cyberchondria behavior
Source: Cuestiones de Fisioterapia
DOI: 10.48047/cf3jra50
Institution: Bharath University
Language: English
Subfield: General Health Professions
Field: Health Professions
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4408040316