JOMPAC
Journal of Medicine and Palliative Care

Journal of Medicine and Palliative Care (JOMPAC) is an open access scientific journal with independent, unbiased, and double-blind review under international guidelines. The purpose of JOMPAC is to contribute to the literature by publishing articles on health sciences and medicine.

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Original Article
Explainable multimodal imaging–based machine learning for cardiovascular risk stratification in early Parkinson’s disease
Abstract
Aims: This study aimed to characterize convergent biochemical and cardiovascular imaging endophenotypes of atherosclerotic risk in early PD and to implement an interpretable machine-learning architecture integrating multimodal clinical and imaging parameters for precision cardiovascular risk profiling and cardiometabolic classification. Methods: A total of 125 early-stage idiopathic PD patients and age- and sex-matched controls were analyzed. Feature space was reduced using cross-validated Least Absolute Shrinkage and Selection Operator (LASSO) with penalty tuning and stability selection to mitigate multicollinearity. XGBoost, Random Forest, RBF-kernel Support Vector Machine, and Stochastic Gradient Boosting models were trained under a train–hold-out framework with Bayesian hyperparameter optimization. Model performance was assessed via bootstrapping, and interpretability was provided using SHapley Additive exPlanations (SHAP). Results: PD patients showed increased hypertension (54.4%; OR 3.2, p=0.007) and hypercholesterolemia (OR 2.8, p=0.01), with excess left ventricular systolic dysfunction (28.8% vs 0%, p

Keywords : Accelerated atherosclerosis, carotid plaque vulnerability, lymphocyte-to-monocyte ratio, machine learning risk stratification, Parkinson's disease, XGBoost algorithm

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Article available in :
Volume 7, Issue 2, 2026
Page : 313-322
https://doi.org/10.47582/jompac.1882083
Article Information
Received : 04 Şub 2026
Accepted : 28 Şub 2026
Published : 27 Mar 2026
Corresponding Author :

Esra Demir Ünal: Department of Neurology, Ankara Yıldırım Beyazıt University Yenimahalle Training and Research Hospital, Ankara, Turkiye

[email protected]
Citation : Demir Ünal E, Arslan AK. Explainable multimodal imaging–based machine learning for cardiovascular risk stratification in early Parkinson’s disease. J Med Palliat Care. 2026;7(2):313-322. doi:10.47582/jompac.1882083

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