Biovision Ai: A Multi-Agent Advanced Multi-Organ Health Prediction System Using Blood Analysis and Medical Imaging

Abstract

Early and accurate detection of multi-organ diseases is a critical challenge in modern healthcare due to the increasing complexity of medical data and the need for integrated diagnostic systems. This paper presents BioVision AI, a Multi-Agent Advanced Multi-Organ Health Prediction System that combines blood test analysis and medical imaging to provide intelligent, comprehensive, and explainable disease prediction. The proposed framework employs a collaborative multi-agent architecture in which specialized agents perform dedicated healthcare tasks including data acquisition, preprocessing, blood parameter analysis, medical image interpretation, organ-specific disease prediction, decision fusion, and automated report generation. The Blood Analysis Agent evaluates clinical biomarkers such as glucose, hemoglobin, cholesterol, creatinine, liver enzymes, and white blood cell count to identify abnormalities related to diabetes, cardiovascular disease, liver disorders, kidney dysfunction, and hematological conditions. Simultaneously, the Medical Imaging Agent utilizes deep learning-based convolutional neural networks to analyze X-ray, MRI, CT, and ultrasound images for detecting structural and pathological abnormalities across multiple organs. The Organ Prediction Agent integrates multimodal outputs from laboratory and imaging data using ensemble learning and feature fusion techniques to generate accurate disease predictions and risk assessments. To enhance reliability and transparency, the system incorporates an Explainable AI Agent that provides interpretable insights through visualization techniques such as SHAP analysis and Grad-CAM heatmaps, enabling healthcare professionals to understand the reasoning behind predictions. A Decision-Making Agent further coordinates the outputs of all intelligent agents to produce severity scores, diagnostic recommendations, and comprehensive health reports. Experimental evaluation demonstrates that BioVision AI achieves improved diagnostic accuracy, faster prediction performance, and enhanced clinical decision support compared with conventional single-source healthcare prediction systems. The proposed framework offers a scalable and intelligent solution for early disease detection, preventive healthcare, and AI-assisted medical diagnosis in hospitals, diagnostic centers, and remote healthcare environments..