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Curevia: Neural and Vision Care

1Moaksha Mehta, 2Jigyanshu, 3Hemlata
1Research Scholar, 2Research Scholar, 3Assistant Professor Panipat Institute of Engineering &
Technology, PIET, Samalkha, Panipat

Abstract: Intelligent healthcare solutions that improve early disease identification and diagnostic accuracy have been made possible by the quick developments in AI and ML. This study introduces CUREVIA, an AI-powered healthcare system that uses medical image analysis to aid in the early detection and evaluation of brain tumors and eye conditions. In order to accurately identify illness patterns and underlying health markers, the system uses supervised machine learning algorithms to evaluate OCT pictures for identifying anomalies connected to the eyes and MRI scans for identifying brain tumors. By guaranteeing accurate interpretation of medical images, the intelligent diagnostic module reduces reliance on human analysis and supports prompt clinical insights. Simultaneously, CUREVIA goes beyond disease detection by integrating a personalized health monitoring framework that offers lifestyle recommendations, treatment recommendations, and testrecommendations based on personal health patterns. The system incorporates image preprocessing, categorization, and result visualization via an intuitive interface and is built with Python-based machine learning models. Patient-related data may be systematically stored and retrieved thanks to the database-driven architecture, which guarantees effective communication and ongoing health monitoring. Curevia fills the gap between proactive health management and diagnostic help by fusing medical image analysis with individualized healthcare support. Curevia is a useful AI-enabled solution for contemporary healthcare systems because of its integrated approach, which improves early diagnosis, decision-making, and preventative healthcare practices.
Keywords: Machine learning, early diagnosis, brain tumor detection, eye disease detection, and medical image analysis.