Advanced AI in Health Care

Description

Advanced AI in Health Care Course Description Master the cutting-edge intersection of artificial intelligence and healthcare with this comprehensive course designed for medical professionals, healthcare data scientists, and AI practitioners entering the medical field. From understanding biomedical data fundamentals to building sophisticated multimodal AI systems, you'll gain the technical expertise to develop, evaluate, and deploy AI solutions that improve patient outcomes. What You'll Learn: You'll start by exploring medical data types—from ECG signals to MRI scans—and setting up professional-grade AI development environments. Progress through deep learning fundamentals tailored specifically for healthcare applications, including neural network architectures, interpretability methods, and handling imbalanced medical datasets. Master computer vision techniques for medical imaging, from pneumonia detection in chest X-rays to precise tumor segmentation in CT scans using CNNs, ResNet, and YOLO. Learn critical concepts like explainable AI (LIME, SHAP, Grad-CAM), bias detection, and clinical validation. Finally, discover how multimodal AI combines imaging, clinical text, and patient history to revolutionize diagnosis and treatment planning. Who This Course Is For: This course is ideal for healthcare professionals seeking to understand AI applications in medicine, data scientists transitioning into healthcare AI, biomedical engineers, and medical students interested in computational medicine. Why It's Valuable: With hands-on projects using real medical data, you'll bridge the gap between AI theory and clinical practice, learning not just how to build models, but how to ensure they're interpretable, unbiased, and ready for real-world healthcare deployment.