Explainable machine learning of PROGRESS-Plus social factors predicts cognitive trajectories after traumatic brain injury.

Overview

Authors: Jingwen Xu^1,2, Urooba Shaikh¹, Thaisa Tylinski Sant’Ana^1,3, Tatyana Mollayeva^1,4,5,6,7

ORCID iDs: Jingwen Xu, Urooba Shaikh, Thaisa Tylinski Sant’Ana, Tatyana Mollayeva

KITE Toronto Rehabilitation Institute, University Health Network,Toronto, ON Canada
Faculty of Applied Science and Engineering, University of Toronto,Toronto, ON Canada
Institute for Management and Innovation, University of Toronto Mississauga,Mississauga, ON Canada
Dalla Lana School of Public Health, University of Toronto,Toronto, ON Canada
Rehabilitation Sciences Institute, Temerty Faculty of Medicine, University of Toronto,Toronto, ON Canada
Department of Occupational Science and Occupational Therapy, Temerty Faculty of Medicine, University of Toronto,Toronto, ON Canada
Global Brain Health Institute, Trinity College Dublin,Dublin, Ireland

Institutions: University Health Network (Canada); University of Toronto (Canada); Trinity College Dublin (Ireland)

Journal: Scientific reports, volume 16, issue 1, article 10629

Dates: received 12 January 2026; accepted 16 March 2026; published online 30 March 2026

Type: Research article · Language: English

License: CC BY-NC-ND

Identifiers: DOI 10.1038/s41598-026-44818-5 · PMID 41912580 · PMCID PMC13039392 · OpenAlex W7143529055

Open access: gold, a free copy (OpenAlex)

Status: empty repository (how the code is found and verified)

Categories: human (organism), traumatic brain injury (population)

Methods: Connectivity, Machine learning

Keywords: Artificial intelligence, Common data elements, Data harmonization, Evidence gap, Information management, Social determinants of health, Medical research, Neurology, Neuroscience

MeSH: Brain Injuries, Traumatic*, Cognition*, Machine Learning*, Adult, Boosting Machine Learning Algorithms, Humans, Male, Prediction Algorithms, Predictive Learning Models, Prognosis, Random Forest (* major topic)

Topic: Traumatic Brain Injury Research (Clinical Neurology, Medicine), according to OpenAlex

Funding: Gouvernement du Canada | Canadian Institutes of Health Research (IRSC) (202306BK5-510306-BKS-ADHD-220229); Canada Research Chairs (CRC-2021-00074)

Citations: cited by 1 paper (Europe PMC); 91 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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OSF 5sjvx

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State: the link answers, verified on 30 September 2026

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Size: 4 files, 0 scripts

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Found in: the references

Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation

Availability: 1 check, the latest on 30 September 2026: the link answers (HTTP 200)

30 September 2026: the link answers (HTTP 200)

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Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 4 authors, 9 keywords, 11 MeSH terms, 2 funders, 85 references.

Cite

This paper

Xu, J., Shaikh, U., Tylinski Sant’Ana, T., & Mollayeva, T. (2026). Explainable machine learning of PROGRESS-Plus social factors predicts cognitive trajectories after traumatic brain injury. Scientific reports, 16(1), 10629. https://doi.org/10.1038/s41598-026-44818-5

BibTeX

@article{xu2026explainable, author = {Xu, Jingwen and Shaikh, Urooba and Tylinski Sant’Ana, Thaisa and Mollayeva, Tatyana}, title = {{Explainable machine learning of PROGRESS-Plus social factors predicts cognitive trajectories after traumatic brain injury}}, journal = {Scientific reports}, year = {2026}, month = mar, volume = {16}, number = {1}, pages = {10629}, publisher = {Nature Publishing Group}, issn = {2045-2322}, doi = {10.1038/s41598-026-44818-5}, url = {https://doi.org/10.1038/s41598-026-44818-5}, pmid = {41912580}, pmcid = {PMC13039392} }

RIS

TY - JOUR AU - Xu, Jingwen AU - Shaikh, Urooba AU - Tylinski Sant’Ana, Thaisa AU - Mollayeva, Tatyana TI - Explainable machine learning of PROGRESS-Plus social factors predicts cognitive trajectories after traumatic brain injury T2 - Scientific reports J2 - Sci Rep PY - 2026 DA - 2026/03/30 VL - 16 IS - 1 SP - 10629 SN - 2045-2322 PB - Nature Publishing Group DO - 10.1038/s41598-026-44818-5 UR - https://doi.org/10.1038/s41598-026-44818-5 LA - en ER -

CSL-JSON

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