OSCR

Interpretable machine learning for Parkinson's disease diagnosis, staging, and biological mechanism exploration: a multicenter analysis.

Overview

Authors: Lu Hao1, Zihao Wang2, Yutong Zhu1, Xizheng Wang1, Minghui Zhu1, Kalibunuer Mahemuti1, Yangtai Guan3
  1. Department of Medical Imaging Center, The Second Affiliated Hospital of Xinjiang Medical University,Urumqi, 830011 China
  2. Department of Neurology, The Second Affiliated Hospital of Xinjiang Medical University,Urumqi, 830011 China
  3. Department of Neurology, The Affiliated Renji Hospital of Shanghai Jiao Tong University,Shanghai, 200000 China
Institutions: Second Affiliated Hospital of Xinjiang Medical University (China); Shanghai Jiao Tong University (China)
Journal: BioData mining, volume 19, issue 1, article 79
Dates: received 20 February 2026; accepted 1 June 2026; published online 26 June 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1186/s13040-026-00574-w · PMID 42363244 · PMCID PMC13579904 · OpenAlex W7166130203
Open access: gold, a free copy (OpenAlex)
Status: dead link
Categories: genetics / omics (modality), Parkinson's (population)
Methods: Connectivity, Spectral & time-frequency, Statistics, Machine learning, Preprocessing, fMRI & imaging, Physiology & signal measures
Keywords: Parkinson’s disease, Radiomics, Machine learning, Interpretability, Multicenter study
Topic: Parkinson's Disease Mechanisms and Treatments (Neurology, Medicine), according to OpenAlex
Funding: Xinjiang Uygur Autonomous Region "2+5" Key Talent Program "Tianshan Talent" Medical and Health High-level Talents Project (TSYC202401B159); Xinjiang Uygur Autonomous Region Tianshan Talent Science and Technology Innovation Leading Talents Program (2022197449); Xinjiang Uygur Autonomous Region Natural Science Foundation Project (2024D01C47)
Citations: not cited yet (Europe PMC); 36 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

No file of the authors' code could be read here: it is described below, and read at its source.

jy2137/PD-radiomics

License: none: the authors keep all their rights
State: the link is dead, verified on 27 September 2026
Evidence: found in the paper
Software Heritage: not archived
Found in: the text, “Model construction and evaluation”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link is dead
  • 27 September 2026: the link is dead
At the source: github.com/jy2137/PD-radiomics

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 0 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Code and data availability statement

The paper has a code and data 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 data are available on request
  • it says that the code is available on request

Read it in the paper: doi.org/10.1186/s13040-026-00574-w.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 7 authors, 5 keywords, 3 funders, 31 references.

Cite

This paper

Hao, L., Wang, Z., Zhu, Y., Wang, X., Zhu, M., Mahemuti, K., & Guan, Y. (2026). Interpretable machine learning for Parkinson's disease diagnosis, staging, and biological mechanism exploration: a multicenter analysis. BioData mining, 19(1), 79. https://doi.org/10.1186/s13040-026-00574-w

BibTeX

@article{hao2026interpretable,
author = {Hao, Lu and Wang, Zihao and Zhu, Yutong and Wang, Xizheng and Zhu, Minghui and Mahemuti, Kalibunuer and Guan, Yangtai},
title = {{Interpretable machine learning for Parkinson's disease diagnosis, staging, and biological mechanism exploration: a multicenter analysis}},
journal = {BioData mining},
year = {2026},
month = jun,
volume = {19},
number = {1},
pages = {79},
publisher = {BMC},
issn = {1756-0381},
doi = {10.1186/s13040-026-00574-w},
url = {https://doi.org/10.1186/s13040-026-00574-w},
pmid = {42363244},
pmcid = {PMC13579904}
}

RIS

TY - JOUR
AU - Hao, Lu
AU - Wang, Zihao
AU - Zhu, Yutong
AU - Wang, Xizheng
AU - Zhu, Minghui
AU - Mahemuti, Kalibunuer
AU - Guan, Yangtai
TI - Interpretable machine learning for Parkinson's disease diagnosis, staging, and biological mechanism exploration: a multicenter analysis
T2 - BioData mining
J2 - BioData Min
PY - 2026
DA - 2026/06/26
VL - 19
IS - 1
SP - 79
SN - 1756-0381
PB - BMC
DO - 10.1186/s13040-026-00574-w
UR - https://doi.org/10.1186/s13040-026-00574-w
LA - en
ER -

CSL-JSON

{
"id": "10.1186/s13040-026-00574-w",
"type": "article-journal",
"title": "Interpretable machine learning for Parkinson's disease diagnosis, staging, and biological mechanism exploration: a multicenter analysis",
"container-title": "BioData mining",
"author": [
{
"family": "Hao",
"given": "Lu"
},
{
"family": "Wang",
"given": "Zihao"
},
{
"family": "Zhu",
"given": "Yutong"
},
{
"family": "Wang",
"given": "Xizheng"
},
{
"family": "Zhu",
"given": "Minghui"
},
{
"family": "Mahemuti",
"given": "Kalibunuer"
},
{
"family": "Guan",
"given": "Yangtai"
}
],
"container-title-short": "BioData Min",
"volume": "19",
"issue": "1",
"page": "79",
"DOI": "10.1186/s13040-026-00574-w",
"PMID": "42363244",
"PMCID": "PMC13579904",
"ISSN": "1756-0381",
"publisher": "BMC",
"URL": "https://doi.org/10.1186/s13040-026-00574-w",
"language": "en",
"issued": {
"date-parts": [
[
2026,
6,
26
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1038/s41531-026-01408-6 [code]
A stacked multi-classifier for multi-modal data fusion in transcranial sonography-based Parkinson's disease assessment.
Journal: NPJ Parkinson's disease
In common: Parkinson's, 3 references
[2] doi:10.1038/s41531-026-01360-5 [code]
Hippocampal atrophy in untreated de novo Parkinson's disease with obstructive sleep apnea.
Journal: NPJ Parkinson's disease
In common: Parkinson's, 2 references
[3] doi:10.1002/mds.70334
A Brainstem Radiomics Framework to Distinguish Progressive Supranuclear Palsy from Parkinson's Disease.
Journal: Movement disorders : official journal of the Movement Disorder Society
In common: Parkinson's, 2 references
[4] doi:10.1016/j.prdoa.2026.100480 [code]
Multitype hand writing as a digital marker for Parkinson's disease.
Journal: Clinical parkinsonism & related disorders
In common: Parkinson's, 2 references
[5] doi:10.3390/ijms27167140
Astrocytic HSP90AA1 Upregulation and Altered Synaptic Signaling in Parkinson's Disease: Transcriptomic Screening and In Vivo Validation.
Journal: International journal of molecular sciences
In common: Parkinson's, genetics / omics, 1 reference
[6] doi:10.3389/fnins.2026.1862571
Integrated bulk, single-cell, and spatial transcriptomic analyses prioritize NOTCH1 as a candidate gene associated with neurovascular and immune-related alterations in Parkinson's disease.
Journal: Frontiers in neuroscience
In common: Parkinson's, genetics / omics, 1 reference
[7] doi:10.1007/s12031-026-02506-z
Striatal Dysregulation of Angpt2 and Circadian Gene Expression in a Rotenone Rat Model of Parkinson's Disease.
Journal: Journal of molecular neuroscience : MN
In common: Parkinson's, genetics / omics, 1 reference
[8] doi:10.3389/frai.2026.1807209
A quantum-classical dual-track deep learning network for explainable Parkinson's disease classification.
Journal: Frontiers in artificial intelligence
In common: Parkinson's, 1 reference
[9] doi:10.3389/fnagi.2026.1931183 [code]
A validated workflow for paired total and small RNA sequencing from low-input submandibular gland biopsy specimens in <i>de novo</i> Parkinson's disease patients.
Journal: Frontiers in aging neuroscience
In common: Parkinson's, genetics / omics, 1 reference
[10] doi:10.1016/j.apsb.2026.06.016
Rhynchophylline rewires DLAT lipoylation <i>via</i> conformational control to reverse mitochondrial bioenergetic collapse against dopaminergic neuronal injury.
Journal: Acta pharmaceutica Sinica. B
In common: Parkinson's, genetics / omics, 1 reference

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.