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Doctor Dok is an AI based medical data framework and patient's med vault. Parse any health related PDF/Image to JSON and then use Chat GPT / LLama to discuss it! WARNING: Don't decide on your health based on AI Chat - it's just for Research purposes.
A RESTful API using Flask and XGBoost to predict diabetes in Pima Indians based on various diagnostic measurements. Includes training, saving the best model, and testing the API using Python requests.
💪 Solutech is a web app built with Next.js and JavaScript that automates health calculations like BMI, body fat percentage, and BMR. It helps users track progress, prevent diseases, and maintain healthy habits.
Medicano: A versatile medical application aimed at delivering comprehensive information about medications. It provides users with detailed insights into drug uses, pricing, alternatives, and availability. Key features include a powerful search function, personalized recommendations, a symptom checker, and integration with health articles and news.
Kidney Disease Classifier is a web application that utilizes a fine-tuned VGG16 model to analyze CT scan images and predict tumor presence with 89% accuracy. It features an intuitive interface for image uploads and instant results. Built with Flask, TensorFlow, and MLflow, it showcases deep learning principles in health tech.
Early Detection of Diabetic Kidney Disease using Contrast Enhanced Ultrasound Perfusion Parameters. Explore perfusion models (Lagged Normal, Log-Normal, Gamma Variate), compare their effectiveness, and analyze their application to diabetic and control cases.
Obese-tree is a GitHub repository showcasing the application of a Support Vector Machine (SVM) model to estimate obesity levels based on eating habits and physical condition. Explore the code, data, and Jupyter notebooks to learn how SVM can be used for predictive modeling in the context of health and wellness.
Sehati is a mental health app designed to help users manage their well-being through stress assessments, informative articles, and personalized profiles. Developed for the Software Engineering course, it aims to provide better mental health support through an improved user experience and expanded features.