MORA: An Intelligent Healthcare Platform Integrating Artificial Intelligence for Cardio-Renal Risk Prediction and Remote Patient Monitoring
| dc.contributor.author | Necaibia, Mountassar Billah | |
| dc.date.accessioned | 2026-10-29T12:35:37Z | |
| dc.date.available | 2026-10-29T12:35:37Z | |
| dc.date.issued | 2026-06-21 | |
| dc.description.abstract | Background: The global rise of chronic non-communicable diseases (NCDs), particularly Chronic Heart Failure (CHF) and Chronic Kidney Disease (CKD), represents one of the most pressing challenges facing contemporary healthcare systems. These conditions frequently coexist as a complex cardio-renal syndrome, demanding continuous, integrated clinical management rather than isolated, episodic interventions. Traditional healthcare infrastructures, designed primarily for acute care, are increasingly strained by the longitudinal demands of chronic disease monitoring. Objective: This research develops MORA, an AI-powered platform for real-time remote monitoring and early risk stratification of patients affected by CHF and CKD, with a focus on the cardio-renal axis. Methodology: The platform integrates remote patient monitoring (RPM) with electronic health records (EHR) to create a continuous, longitudinal data pipeline. Machine learning algorithms including gradient boosting and deep learning architectures are employed to model disease progression and generate predictive risk scores. Explainable AI (XAI) techniques, specifically SHAP and LIME, are incorporated to ensure that model outputs are clinically interpretable and trustworthy for healthcare professionals. Results: Evaluations demonstrate that MORA effectively aggregates heterogeneous health data and delivers accurate, timely predictive insights. The integration of XAI significantly enhances clinician trust and supports informed clinical decision-making. The platform successfully bridges the gap between raw patient data and actionable preventive interventions. Conclusion: MORA enables a paradigm shift from reactive to preventive chronic disease management, with meaningful potential to improve patient outcomes through timely clinical intervention. The platform provides a scalable, interoperable foundation for the future of AI-assisted digital healthcare. | |
| dc.identifier.uri | https://dspace.univ-tlemcen.dz/handle/112/27228 | |
| dc.language.iso | en | |
| dc.publisher | University of Tlemcen | |
| dc.relation.ispartofseries | N°inventaire 2920 | |
| dc.subject | Artificial Intelligence | |
| dc.subject | Chronic Heart Failure | |
| dc.subject | Chronic Kidney Disease | |
| dc.subject | Remote Patient Monitoring | |
| dc.subject | Predictive Analytics | |
| dc.subject | Explainable AI | |
| dc.subject | Cardio-Renal Syndrome | |
| dc.subject | Biomedical Engineering. | |
| dc.title | MORA: An Intelligent Healthcare Platform Integrating Artificial Intelligence for Cardio-Renal Risk Prediction and Remote Patient Monitoring | |
| dc.type | Thesis |
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