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Artificial Intelligence in Enhancing Syncope Management - An Update.
Aamir, Alifiya; Jamil, Yumna; Bilal, Maham; Diwan, Mufaddal; Nashwan, Abdulqadir J; Ullah, Irfan.
  • Aamir A; Dow University of Health Sciences, Karachi, Pakistan.
  • Jamil Y; Dow University of Health Sciences, Karachi, Pakistan.
  • Bilal M; Dow University of Health Sciences, Karachi, Pakistan.
  • Diwan M; Dow University of Health Sciences, Karachi, Pakistan.
  • Nashwan AJ; Hamad Medical Corporation, Doha, Qatar. Electronic address: anashwan@hamad.qa.
  • Ullah I; Kabir Medical College, Gandhara University, Peshawar, Pakistan; Department of Internal Medicine, Khyber Teaching Hospital, Peshawar, Pakistan.
Curr Probl Cardiol ; 49(1 Pt B): 102079, 2024 Jan.
Article en En | MEDLINE | ID: mdl-37716544
ABSTRACT
This review looks into the use of Artificial Intelligence (AI) in the management of syncope, a condition characterized by a brief loss of consciousness caused by cerebral hypoperfusion. With rising prevalence, high costs, and difficulty in diagnosis and risk stratification, syncope poses significant healthcare challenges. AI has the potential to improve symptom differentiation, risk assessment, and patient management. Machine learning, specifically Artificial Neural Networks, has shown promise in accurate risk stratification. AI-powered clinical decision support tools can improve patient evaluation and resource utilization. While AI holds great promise for syncope management, challenges such as data quality, class imbalance, and defining risk categories remain. Ethical concerns about patient privacy, as well as the need for human empathy, complicate AI integration. Collaboration among data scientists, clinicians, and ethics experts is critical for the successful implementation of AI, which has the potential to improve patient outcomes and healthcare efficiency in syncope management.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Síncope / Inteligencia Artificial Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Síncope / Inteligencia Artificial Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2024 Tipo del documento: Article