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Advanced Deep Learning Methods for Healthcare
University of Illinois at Urbana-Champaign via Coursera
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Overview
The “Advanced Deep Learning Methods for Healthcare” course delves into cutting-edge deep learning techniques tailored to address complex challenges in the healthcare domain. Designed for data scientists, researchers, and healthcare professionals, this course focuses on leveraging advanced neural network architectures to improve diagnostics, treatment planning, and patient outcomes. Participants will explore sophisticated models such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, and attention mechanisms, applying them to medical imaging, electronic health records (EHRs), genomics, and time-series health...
Syllabus
- Week 1 - Attention Models
- Attention Models are useful to detect specific features in a data source. We'll explain how it can be applied to the risk of heart failure.
- Week 2 - Graph Neural Networks
- In this week we'll explain the fundamentals of Graph Neural Networks.
- Week 3 - Memory Networks
- We'll explain the principles behind Memory Networks and how they can be used for predictions in medical applications.
- Week 4 - Generative Models
- We'll discuss Generative Networks, as well as the method of Variational Autoencoder
University of Illinois at Urbana-Champaign via Coursera
16 hours 28 minutes
Paid Certificate Available
English
On-Demand
Advanced
Instructor
Jimeng Sun
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