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Development and Validation of a SHAP-Interpretable Machine Learning Model for Stroke Risk Prediction Using Circulating MicroRNA Biomarkers

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Bibliographic Details
Published in:Journal of Molecular Neuroscience
Format: Online Article RSS Article
Published: 2026
Subjects:
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container_title Journal of Molecular Neuroscience
description
discipline_display Psychiatry and Neurology
discipline_facet Psychiatry and Neurology
format Online Article
RSS Article
genre Journal Article
id rss_article:59200
institution FRELIP
journal_source_facet Journal of Molecular Neuroscience
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Development and Validation of a SHAP-Interpretable Machine Learning Model for Stroke Risk Prediction Using Circulating MicroRNA Biomarkers
Psychiatry and Neurology
General
Psychiatry and Neurology
sub_discipline_display General
sub_discipline_facet General
subject_display Psychiatry and Neurology
General
Psychiatry and Neurology
Psychiatry and Neurology
General
Psychiatry and Neurology
subject_facet Psychiatry and Neurology
General
Psychiatry and Neurology
title Development and Validation of a SHAP-Interpretable Machine Learning Model for Stroke Risk Prediction Using Circulating MicroRNA Biomarkers
title_auth Development and Validation of a SHAP-Interpretable Machine Learning Model for Stroke Risk Prediction Using Circulating MicroRNA Biomarkers
title_full Development and Validation of a SHAP-Interpretable Machine Learning Model for Stroke Risk Prediction Using Circulating MicroRNA Biomarkers
title_fullStr Development and Validation of a SHAP-Interpretable Machine Learning Model for Stroke Risk Prediction Using Circulating MicroRNA Biomarkers
title_full_unstemmed Development and Validation of a SHAP-Interpretable Machine Learning Model for Stroke Risk Prediction Using Circulating MicroRNA Biomarkers
title_short Development and Validation of a SHAP-Interpretable Machine Learning Model for Stroke Risk Prediction Using Circulating MicroRNA Biomarkers
title_sort development and validation of a shap-interpretable machine learning model for stroke risk prediction using circulating microrna biomarkers
topic Psychiatry and Neurology
General
Psychiatry and Neurology
url https://link.springer.com/article/10.1007/s12031-026-02540-x