Learning outcomes:

Overview of biomedical engineering and the challenges in this field, artificial intelligence and deep learning, introduction to classification- linear regression, kNN, optimization- basic principles , cost functions and optimization methods, neural networks, convolutional neural networks, training neural networks, deep learning software, CNN architectures, recurrent neural networks, detection and segmentation, data augmentation and generation, selected applications: fMRI, mammography, ECG, speech signal processing, additional examples.‬