Σύστημα υποστήριξης αποφάσεων πρόγνωσης, διάγνωσης και θεραπείας για ασθενείς με Parkinson
Date Issued
July 4, 2024
Type
Πτυχιακή Εργασία
Abstract
This thesis focuses on the application of Decision Support Systems in the diagnosis, management, and treatment of Parkinson's disease, aiming to address the challenges in healthcare for patients with this condition. By exploring the potential of DSS in the healthcare sector, innovative solutions are proposed to enhance medical care for individuals with Parkinson's disease. The study includes an extensive literature review utilizing reputable sources such as PubMed, ERIC, JSTOR, IEEE Xplore, and Google Scholar. Specific search keywords like "detection of PD using machine learning (ML)" and "detection of PD using deep learning (DL)" were employed to identify relevant articles. The research emphasizes on the significance of omics methods, computational tools, mathematical modeling, and bio-inspired optimization algorithms in advancing our understanding of Parkinson's disease pathogenesis and identifying potential diagnostic markers. Effective analysis techniques for complex biological data and the role of integrated datasets in mechanistic modeling for neurodegenerative diseases like Parkinson's are underscored.
Subjects