This Flask web application is designed to accurately predict the likelihood of Hypothyroid disease by analyzing specific patient data with advanced machine learning techniques. With high accuracy achieved through optimized hyperparameter tuning, it features a simple, user-friendly interface that enables healthcare professionals to enter patient details and receive reliable predictions. Built for clinical settings, this tool supports early diagnosis and informed decision-making, helping improve patient care with trustworthy, data-driven insights.
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🔍 Automated Prediction
Leverages advanced machine learning classifiers to deliver accurate predictions on Hypothyroid disease, empowering healthcare professionals with data-driven insights. -
🎯 Hyperparameter Tuning for Accuracy
Boosts model precision with optimization techniques like Grid Search and Random Search, ensuring reliable and robust prediction results. -
🌐 User-Centric Interface
Built with Flask, the application provides a seamless, intuitive interface, making it easy for users to input patient data and receive instant predictions. -
⚙️ Flexible Model Integration
Supports a variety of machine learning algorithms, including Random Forest, Support Vector Machine (SVM), and Neural Networks, offering adaptability and options for different prediction needs.
website link: https://hyporthroid-web-app.onrender.com
- Masruk Habib -Team Leader
- Puvanenthirarajah Sathasivam
- Wasihun Ageru