Applications of machine learning tools to real-world problems in biomedical engineering including diagnostic and prognostic applications. An introduction to machine learning. Machine learning tools: regression and classification; manifold learning and dimensional reduction; decision trees and ensemble learning; unsupervised learning and clustering; feature selection and feature extraction; neural networks and deep learning. Biomedical applications: cancer, cardiovascular disease, diabetes, ne...
Applications of machine learning tools to real-world problems in biomedical engineering including diagnostic and prognostic applications. An introduction to machine learning. Machine learning tools: regression and classification; manifold learning and dimensional reduction; decision trees and ensemble learning; unsupervised learning and clustering; feature selection and feature extraction; neural networks and deep learning. Biomedical applications: cancer, cardiovascular disease, diabetes, ne...
