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Deep Learning for Healthcare Lecture series

HomeDeep Learning for Healthcare Lecture series
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Deep Learning for Healthcare Lecture series

by Usman Akhtaron 3 January 2020in

This lecture series is part of the Asi@Connect project Intelligent Medical Services over TEIN.

Deep Learning (DL) has the potential to change the future of healthcare. The use of Artificial Intelligence (AI) has become increasingly popular and is now used, for example, in cancer diagnosis and treatment. Deep learning for computer vision enables a more precise medical imaging and diagnosis. In this lecture series we will cover the fundamentals of neural networks, along with the application of more advanced neural models in medical imaging. Furthermore, both Pytorch and Tensorflow hands-on tutorials will be provided as well.

Course Content

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Lessons Status
1

Deep Learning Introduction
  • This lecture will provide basic overview of neural networks family of algorithms evolution.

2

Convolutional Neural Networks (CNN) for Medical Images
  • This lecture will describe the process of CNN and its working on medical imaging.

3

Recurrent Neural Networks (RNN)
  • This lecture will describe the working of RNN with medical domain applications.

4

Pytorch Tutorial
  • This lecture will demonstrate the use of Pytorch in working on medical domain.

5

Tensorflow Tutorial
  • This lecture will demonstrate the use of Tensorflow in working on medical domain.

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Written by Usman Akhtar

Hello, i have been involved in research and development activity mainly in the area of distributed systems.

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The UCLab. at the Kyung Hee University is consisted of more than 30 Post-doc, Ph.D and Master students, working on research projects under the supervision of Prof. Sungyoung Lee, who studied in the field of ubiquitous systems.

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