3.0

credits

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This class will provide a background on deep learning theory and describe how to leverage deep learning models for imaging research. This includes classification and segmentation of clinical medical imaging data, as well as multimodal data analysis. Students will get hands-on experience in working with medical images and learn how to integrate AI models in clinical research.  Learning goals include: Be able to identify the components of building a deep neural network; Understand how to use neural networks for medical image and multimodal analysis; Understand how data affects model training and how to create a well-defined dataset and/or utilize pre-trained models; Experiment with creating deep learning models and learn how to evaluate their performance.