An evolving machine-learning-based algorithm to early predict response to anti-CGRP monoclonal antibodies in patients with migraine
The response prediction tool utilizing evolving ML-based models holds promise in the early prediction of treatment outcomes for patients with migraine undergoing anti-CGRP mAbs treatment.
Authors
- Pierangelo Geppetti (ORCID: https://orcid.org/0000-0003-3797-8371)
- David García‐Azorín (ORCID: https://orcid.org/0000-0002-3132-1064)
- Alberto Chiarugi (ORCID: https://orcid.org/0000-0003-1022-2435)
- Catello Vollono (ORCID: https://orcid.org/0000-0001-9371-8035)
- Luigi Francesco Iannone (ORCID: https://orcid.org/0000-0003-3598-0195)
- Andrea Burgalassi (ORCID: https://orcid.org/0009-0001-7028-7735)
- Giulia Vigani (ORCID: https://orcid.org/0009-0000-0425-8170)
- Paolo Calabresi (ORCID: https://orcid.org/0000-0003-0326-5509)
- Ammar Lokhandwala
Institutions
- Università Cattolica del Sacro Cuore (IT)
- Universidad de Valladolid (ES)
- Agostino Gemelli University Polyclinic (IT)
- Azienda Ospedaliero-Universitaria Careggi (IT)
- Istituti di Ricovero e Cura a Carattere Scientifico (IT)
- Hospital Clínico Universitario de Valladolid (ES)
- University of Florence (IT)
- New York University (US)
- Drexel University (US)
Publication Details
- Journal
- Cephalalgia
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1177/03331024241262751
- Citations
- 11
- Primary Topic
- Migraine and Headache Studies
- Type
- article
- Field-Weighted Citation Impact
- 4.24