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Machine Learning Assessment of Next-Day Migraine Likelihood Using Data From 53,000 App Users Living With Migraine

Year: 2026

Type: article

Abstract: The ability to anticipate an impending migraine attack has the potential to improve patients' well-being, yet previous models have shown limited performance. The current study aimed to develop and evaluate a machine learning (ML) model to identify risk of next-day migraine attacks based on electronic diaries, leveraging the longest preattack time frame (30 days) and the largest prospective dataset of patients with migraine (over 53,000) to date.

Source: Neurology Open Access

DOI: 10.1212/wn9.0000000000000144

Authors: Liron Rabany, Anastasia Markina, Robert P. Cowan, Christopher L. Robinson, Shira Shalev-Aviad, Ronen Jashek, Alit Stark-Inbar, Alon Ironi, Peter J. Goadsby

Institutions: Theranica Bio-Electronics Ltd. (Israel), Stanford University, Johns Hopkins University, King's College London, South London and Maudsley NHS Foundation Trust, National Institute for Health and Care Research, King Abdullah University of Science and Technology

Language: English

Topic: Migraine and Headache Studies

Subfield: Psychiatry and Mental health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W7203878923

FWCI:

Cites: 21

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