Concepedia

Machine‐learning‐based approach for predicting response to anti‐calcitonin gene‐related peptide (<scp>CGRP)</scp> receptor or ligand antibody treatment in patients with migraine: A multicenter Spanish study

Alicia González‐Martínez, Josué Pagán, Ancor Sanz‐García, David García‐Azorín, Jaime Rodríguez‐Vico, Alex Jaimes, Andrea Gómez García, Javier Díaz de Terán, N. González-García, Sonia Quintas,

European Journal of Neurology · 2022 · 42 citations · 34 references

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Abstract

Our results show that ML models can predict anti-CGRP response at 6, 9 and 12 months. This study provides a predictive tool that can be used in a real-world setting.

References

34

Greedy function approximation: A gradient boosting machine.

Jerome H. Friedman · The Annals of Statistics · 2001 · 27.3K citations · Full text

, , +13

Headache Classification Committee of the International Headache Society (IHS) The International Classification of Headache Disorders, 3rd edition

Cephalalgia · 2018 · 10.1K citations · Full text

, , +17

A Unified Approach to Interpreting Model Predictions

Scott Lundberg, Su‐In Lee · arXiv (Cornell University) · 2017 · 7.6K citations · Full text

, , +21

Fremanezumab for the Preventive Treatment of Chronic Migraine

Stephen D. Silberstein, David W. Dodick, Marcelo E. Bigal et al. · New England Journal of Medicine · 2017 · 768 citations

Safety and efficacy of erenumab for preventive treatment of chronic migraine: a randomised, double-blind, placebo-controlled phase 2 trial

Stewart J. Tepper, Messoud Ashina, Uwe Reuter et al. · The Lancet Neurology · 2017 · 726 citations

, , +7