Journal of Health & Medical Informatics

Early Identification of Chronic Renal Failure and Enhanced Assistance with Medical Diagnosis

Abstract

Elmi Saleban Yassin*, Ali Yahyaoui and Fatima Ezzahra Ben Bouazaz

Chronic Kidney Disease (CKD) is a progressive and irreversible deterioration in renal function, characterized by a fall in Glomerular Filtration Rate (GFR). It may result from chronic kidney disease or incomplete recovery from acute kidney injury. CKD is a major public health problem, with a worldwide prevalence estimated at between 8% and 16%, mainly affecting the elderly in developed countries, where vascular nephropathy is the main cause. In sub-Saharan Africa, CKD affects more young adults, with a variety of causes. The integration of Artificial Intelligence (AI) into CKD diagnosis and management represents a significant opportunity to improve early detection and patient follow-up. AI algorithms can analyze ultrasound data and other biomarkers to identify signs of CKD before the onset of clinical symptoms, enabling earlier and more personalized interventions. In addition, AI can help predict disease progression and optimize treatment plans, contributing to better management of CKD patients.