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The Clinical Relevance of Artificial Intelligence in Migraine.
Torrente, Angelo; Maccora, Simona; Prinzi, Francesco; Alonge, Paolo; Pilati, Laura; Lupica, Antonino; Di Stefano, Vincenzo; Camarda, Cecilia; Vitabile, Salvatore; Brighina, Filippo.
Afiliación
  • Torrente A; Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), University of Palermo, 90127 Palermo, Italy.
  • Maccora S; Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), University of Palermo, 90127 Palermo, Italy.
  • Prinzi F; Neurology Unit, ARNAS Civico di Cristina and Benfratelli Hospitals, 90127 Palermo, Italy.
  • Alonge P; Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), University of Palermo, 90127 Palermo, Italy.
  • Pilati L; Department of Computer Science and Technology, University of Cambridge, Cambridge CB2 1TN, UK.
  • Lupica A; Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), University of Palermo, 90127 Palermo, Italy.
  • Di Stefano V; Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), University of Palermo, 90127 Palermo, Italy.
  • Camarda C; Neurology and Stroke Unit, P.O. "S. Antonio Abate", 91016 Trapani, Italy.
  • Vitabile S; Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), University of Palermo, 90127 Palermo, Italy.
  • Brighina F; Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), University of Palermo, 90127 Palermo, Italy.
Brain Sci ; 14(1)2024 Jan 16.
Article en En | MEDLINE | ID: mdl-38248300
ABSTRACT
Migraine is a burdensome neurological disorder that still lacks clear and easily accessible diagnostic biomarkers. Furthermore, a straightforward pathway is hard to find for migraineurs' management, so the search for response predictors has become urgent. Nowadays, artificial intelligence (AI) has pervaded almost every aspect of our lives, and medicine has not been missed. Its applications are nearly limitless, and the ability to use machine learning approaches has given researchers a chance to give huge amounts of data new insights. When it comes to migraine, AI may play a fundamental role, helping clinicians and patients in many ways. For example, AI-based models can increase diagnostic accuracy, especially for non-headache specialists, and may help in correctly classifying the different groups of patients. Moreover, AI models analysing brain imaging studies reveal promising results in identifying disease biomarkers. Regarding migraine management, AI applications showed value in identifying outcome measures, the best treatment choices, and therapy response prediction. In the present review, the authors introduce the various and most recent clinical applications of AI regarding migraine.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Brain Sci Año: 2024 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Brain Sci Año: 2024 Tipo del documento: Article País de afiliación: Italia