Health Misinformation Detection: Approaches, Challenges and Opportunities.

To mitigate the rapid spread of health misinformation and its negative impact, this study presents a comprehensive literature review on health misinformation detection. A systematic search is conducted using the Google Scholar database, targeting publications from January 2016 to February 2025. Incl...

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Detalles Bibliográficos
Publicado en:	Inquiry (00469580) Vol. 62; pp. 1 - 36
Autores principales:	Feng, Xiaoye, Luo, Jia, Yang, Yang, El Baz, Didier, Shi, Lei
Formato:	Artículo
Publicado:	Sage Publications Inc. 11/4/2025
Materias:	Boosting algorithms Social media Health literacy Medical logic Random forest algorithms Language & languages Crowdsourcing Data analysis Interprofessional relations Disinformation Memory bias Health status indicators Health At-risk people Privacy Data curation Health policy Phonological awareness Misinformation Information resources Natural language processing Anxiety Emotions Psychological well-being Affective disorders Blockchains Support vector machines Detection algorithms Intention Psychological stress Trust Artificial neural networks Metadata Psychometrics Mathematical models Machine learning Concepts Semantics Sociodemographic factors Accuracy Resource-limited settings Public health Decision trees Theory Information resources management Algorithms Sensitivity & specificity (Statistics) Medical ethics Social isolation Professional competence Educational attainment Genetics Cognition Generalized anxiety disorder Mental depression Psychosocial factors
Acceso en línea:	Ver este registro en EBSCOhost