“DiagnoMe” Mobile Application for Identifying and Predicting the Chronic Diseases

This research introduces a novel approach to chronic disease prediction and identification u sing advanced machine-learning techniques. It addresses the challenges posed by environmental conditions and lifestyle habits contributing to chronic diseases, emphasizing the importance of early disease identification f or prevention a nd accurate diagnosis. Common chronic diseases like Parkinson's Disease, Cardiovascular Disease, Pneumonia, and Skin Diseases are discussed as requiring lifelong treatments. The study's four key components include an RNN-based model for predicting Parkinson's disease, a comparative study of prediction methods for cardiovascular diseases, a Neural Network-based technique for automated skin disease detection, and an explanation of Automated Chest X-ray Diagnosis through Advanced Deep Learning. These components collectively offer a comprehensive and innovative approach to chronic disease diagnosis, with the goal of developing a mobile application based on highly accurate deep learning models to improve healthcare outcomes.