OSCR

Elucidating biopsychosocial mechanisms in migraine: an integrative analytics approach combining genetics, neuroimaging, and machine learning.

Overview

Authors: Yu-Chen Liu1, Zi-Yue Ma1, Ping-Ting Zhou1, Shu-Yu Wang1, Chuan-Lu Shen1, Zi-Yue Fu1, Fen-Fen Li1, Wei Wang2, Ye-Hai Liu1, Kai-Le Wu1, Liang Zhang1
ORCID iDs: Fen-Fen Li
  1. Department of Otolaryngology, Head and Neck Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, Anhui 230031 People’s Republic of China
  2. Headache Center, Department of Neurology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
Institutions: Anhui Medical University (China); First Affiliated Hospital of Anhui Medical University (China); Sir Run Run Shaw Hospital (China); Zhejiang University (China)
Journal: The journal of headache and pain, volume 27, issue 1, article 67
Dates: received 28 October 2025; accepted 24 February 2026; published online 3 March 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1186/s10194-026-02313-2 · PMID 41772412 · PMCID PMC12961808 · OpenAlex W7133218481
Open access: gold, a free copy (OpenAlex)
Status: code on request
Categories: human (organism), pain (population)
Methods: Connectivity, Statistics, Machine learning, fMRI & imaging
Keywords: Migraine, Neuroimaging, Body mass index, Machine learning
MeSH: Brain*, Machine Learning*, Migraine Disorders*, Neuroimaging*, Data Analytics, Female, Humans, Male, Predictive Learning Models, Random Forest (* major topic)
Topic: Migraine and Headache Studies (Psychiatry and Mental health, Medicine), according to OpenAlex
Funding: University Natural Science Research Project of Anhui Province (2023AH053292)
Citations: cited by 1 paper (Europe PMC); 31 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Code

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Code availability statement

The paper has a code availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

  • it says that the code is available on request

Read it in the paper: doi.org/10.1186/s10194-026-02313-2.

Tracing map

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Data

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Data availability statement

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  • it says that the data are available on request

Read it in the paper: doi.org/10.1186/s10194-026-02313-2.

Versions

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Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 11 authors, 4 keywords, 10 MeSH terms, 1 funder, 31 references.

Cite

This paper

Liu, Y.-C., Ma, Z.-Y., Zhou, P.-T., Wang, S.-Y., Shen, C.-L., Fu, Z.-Y., Li, F.-F., Wang, W., Liu, Y.-H., Wu, K.-L., & Zhang, L. (2026). Elucidating biopsychosocial mechanisms in migraine: an integrative analytics approach combining genetics, neuroimaging, and machine learning. The journal of headache and pain, 27(1), 67. https://doi.org/10.1186/s10194-026-02313-2

BibTeX

@article{liu2026elucidating,
author = {Liu, Yu-Chen and Ma, Zi-Yue and Zhou, Ping-Ting and Wang, Shu-Yu and Shen, Chuan-Lu and Fu, Zi-Yue and Li, Fen-Fen and Wang, Wei and Liu, Ye-Hai and Wu, Kai-Le and Zhang, Liang},
title = {{Elucidating biopsychosocial mechanisms in migraine: an integrative analytics approach combining genetics, neuroimaging, and machine learning}},
journal = {The journal of headache and pain},
year = {2026},
month = mar,
volume = {27},
number = {1},
pages = {67},
publisher = {BMC},
issn = {1129-2369},
doi = {10.1186/s10194-026-02313-2},
url = {https://doi.org/10.1186/s10194-026-02313-2},
pmid = {41772412},
pmcid = {PMC12961808}
}

RIS

TY - JOUR
AU - Liu, Yu-Chen
AU - Ma, Zi-Yue
AU - Zhou, Ping-Ting
AU - Wang, Shu-Yu
AU - Shen, Chuan-Lu
AU - Fu, Zi-Yue
AU - Li, Fen-Fen
AU - Wang, Wei
AU - Liu, Ye-Hai
AU - Wu, Kai-Le
AU - Zhang, Liang
TI - Elucidating biopsychosocial mechanisms in migraine: an integrative analytics approach combining genetics, neuroimaging, and machine learning
T2 - The journal of headache and pain
J2 - J Headache Pain
PY - 2026
DA - 2026/03/03
VL - 27
IS - 1
SP - 67
SN - 1129-2369
PB - BMC
DO - 10.1186/s10194-026-02313-2
UR - https://doi.org/10.1186/s10194-026-02313-2
LA - en
ER -

CSL-JSON

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