What is deep learning and why is it a data-driven approach?
This video is a part of a webinar and will explain what is deep learning is it a data-driven approach (for healthcare and biomedical sciences).
The deep learning models used for image analysis in medical imaging use neural networks. The neural networks are trained with examples instead of with defined features (like it used to be done in the classical machine learning approaches).
We train deep learning models on available data and later want them to make predictions of unseen data. This is a bit of a paradox because the unseen data is rarely identical to the training and test data.
To solve this issue we want to include different aspects of the image data we want to work with and get predictions for in our training set.
Sometimes, if our data sets are small, deep learning might not be the best performing method and we might need to go back or combine it with classical computer vision approaches.
TO WATCH THE FULL WEBINAR CLICK HERE
//CHAPTERS
00:00 - 00:31 - Introduction
00:35 - This video was a part of a webinar for the Davis-Thompson foundation
1:00 - Full Webinar playlist in the card
1:05 - Registration Link for the full webinar:
1:19 - Deep Learning - the data-driven approach what does that mean?
1:27 - What is Deep Learning?
1:54 - Classical machine learning vs deep learning for image analysis
3:57 - Performance of approach vs the amount of data available for training - graph
05:28 - Why does the quality of the training data matters?
5:53 - Registration Link for the full webinar:
5:57 - Full Webinar Playlist in the card
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