Medical Deep Learning: Our 5 Steps to Success

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With our medical data classifications we build the base for medical deep learning. Find out how a medical deep learning algorithm is developed in cooperation with our partners. Read our 5 Steps to Medical Deep Learning Success.

At artificial intelligence congresses we are often asked how we develop our medical deep learning projects. Therefore, we would like to explain our 5 steps programme to you briefly. So don’ t hesitate to get in touch with us, if you are interested in teaming up. 

1. Define Image Data Source

The Telepaxx data center contains 11 petabyte (PB) of medical data. However, we mainly use individual clinic infrastructures and  servers as a data source. Thus ensuring high flexibility and security.

2. Pre-process Image Data

In the second step on our way to success we provide smart data for relevant use case and prepare training data sample.

3. Create Classifier

In this stage our partner comes in to identify optimal algorithms, adjust parameters, train algorithms and finally to find the best classifiers.

4. Medical Workflow Integration

In stage 4 we test the algorithms and classifiers developed by our partners in real-life settings integrating them in our clinical workflows and IT infrastructures.

5. Deliver Value Added Services

In the final stage of our 5 steps to success Telepaxx and their partners provide value added services to clinics, physicians, radiologists, patients and many more.

 

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