Iranian Journal of Biomedical Engineering (IJBME)
نشریه علمی مهندسی پزشکی زیستی

Prediction of Medication Regimens for Patients with Parkinson’s Disease Using Time-Aware Gated Recurrent Units

Document Type : Full Research Paper

Authors

Atiye Riasi 1
Mehdi Delrobaei 2
Mehri Salari 3

1 Ph.D. Student, Department of Biomedical Engineering, Faculty of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran

2 Mechatronics Department, Faculty of Electrical Engineering, K. N. Toosi University of Technology

3 Associate Professor, Department of Neurology, Shahid Beheshti University of Medical Science, Tehran, Iran

https://doi.org/10.22041/ijbme.2025.2075956.2006
Abstract
Managing Parkinson’s disease (PD) through medication can be challenging due to variations in symptoms and disease duration. This study aims to demonstrate the potential of sequence-to-sequence algorithms to suggest personalized medication combinations for patients with PD based on their prior visits. The proposed method employs a multi-layer time-aware gated recurrent unit architecture with a multi-head mechanism to accurately predict the dosage of key PD medications based on patients’ motor symptoms and previously prescribed medications. The time-aware model incorporates a decay factor so that older information from more distant visits has less influence on the current state. Our evaluation demonstrates that the proposed architecture achieves high performance in predicting dosages of main PD medication groups with a mean squared error (MSE) of 0.005, a mean absolute error (MAE) of 0.037, a root mean square error (RMSE) of 0.073, and a coefficient of determination (R²) of 0.75. The proposed architecture provides a foundation for developing intelligent clinical decision support systems and personalized medication management tools, offering a data-driven approach to optimizing treatment regimens for patients with PD.

Keywords

Medication management
Parkinson&‌rsquo
s disease
Personalized medicine
Clinical decision support system
Sequential learning
Iranian Journal of Biomedical Engineering (IJBME)
Volume 19, Issue 2
Summer 2025
Pages 121-130

  • Receive Date 29 October 2025
  • Revise Date 08 December 2025
  • Accept Date 14 December 2025

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