Renal AI: A Hybrid Convergent Ai Framework for Advanced Chronic Kidney Disease Detection and Diagnostic Support

RenalAI is an advanced AI-enhanced diagnostic ecosystem designed for the early and accurate detection of Chronic Kidney Disease (CKD). Manual diagnosis of renal pathologies is often delayed due to the separate analysis of clinical reports and medical imaging. To address this, the project proposes a Hybrid Convergent AI Framework that integrates two powerful models: a Convolutional Neural Network (CNN) for detecting abnormalities in CT scans and a Random Forest Classifier for risk stratification based on clinical biomarkers. The framework employs advanced preprocessing techniques to ensure data integrity across multi-modal inputs. By converging these two modules, RenalAI achieves a high diagnostic accuracy of 95.8%, providing a reliable second opinion for clinicians. Furthermore, the system incorporates a voice-enabled assistant using Speech Recognition and NLP to allow hands-free clinical navigation and automated report generation. RenalAI serves as a critical Diagnostic Support System, reducing human error and significantly improving patient outcomes through precision diagnostics and intelligent automation.