Prediksi penyakit jantung berbasis AI dengan algoritma machine learning untuk analisis kesehatan yang cepat dan akurat.
Didukung oleh Ensemble model Random Forest, Neural Network dan XGBoost untuk hasil prediksi yang lebih tepat dan instan.
Build web-based health prediction tools for hospitals, clinics, and personal use.
Use a single model to build native health apps for iOS and Android platforms.
Build scalable and resilient cloud-native health apps that run on all major providers.
Build smart health apps with TensorFlow, PyTorch, and Azure ML integration.
Our AI model is developed and maintained as an open-source project, the foundation for millions of health predictions worldwide who want to build reliable diagnostic tools together.
You can analyze, predict, and diagnose on multiple devices, including mobile phones, tablets, desktop computers, and medical equipment.
Our platform offers a comprehensive library of learning resources. Access tutorials, research papers, case studies, and content from medical experts to help you build better health prediction models.
Getting started with health AI development? We have you covered with our AI Health for Beginners videos. Explore tutorials on medical data, neural networks, prediction models, machine learning fundamentals, diagnostic algorithms, and more.
Discover your path to build health prediction models with our Medical Research Hub. Whether you're just starting or an experienced medical professional, our research-based approach helps you arrive at your goals faster, with more confidence and accuracy.
Get an introduction to the medical knowledge and skills needed for a career as a health AI developer. Experience comprehensive learning courses that provide a broad perspective on core technologies leveraging medical AI and machine learning.