Machine learning and deep learning have been rapidly adopted in providing solutions to various problems in medicine. If you wish to build scalable machine learning/deep learning-powered healthcare solutions, you need to understand how to use tools to build them.

The TensorFlow is an open source machine learning framework. It enables the use of data flow graphs for numerical computations, with automatic parallelization across several CPUs, GPUs or TPUs. Its architecture makes it ideal for implementing machine learning/deep learning algorithms.

This tutorial will provide hands-on exposure to implement Deep Learning based healthcare solutions using TensorFlow.

 
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Outline/Structure of the Tutorial

  • Brief Introduction to TensorFlow
  • Deep Neural Networks using TensorFlow
  • Implementation of Deep Neural Network based Healthcare Applications using TensorFlow
  • Future Research Directions
  • Conclusions

Learning Outcome

After attending this tutorial, participants will be able to…

  • Build deep learning models using TensorFlow libraries.
  • Develop machine learning/deep learning based healthcare solutions using TensorFlow

Target Audience

Students, faculty members, researchers as well as Industrialists who are working in the field of machine learning/deep learning or wish to start building machine learning/deep learning based applications.

Prerequisites for Attendees

  • Familiarity with fundamentals of machine Learning and matrices.

  • No experience with TensorFlow is required.

schedule Submitted 1 month ago

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  • By  ~  1 month ago
    reply Reply

    Hi, Nicely organized and detailed slide deck. Session seems interesting.

  • Dipanjan Sarkar
    By Dipanjan Sarkar  ~  1 month ago
    reply Reply

    Hi, thanks for the submission, can we get some specifics on what are the exact use-cases \ case-studies from healthcare which would be covered in this proposed session?

    • Dr Mayuri Mehta
      By Dr Mayuri Mehta  ~  1 month ago
      reply Reply

      Hello Dipanjan, I will mainly focus on following topics in this session:

      1. Detection of disease from images/video using deep learning based model (Case Study: Detection of Dry Eye Disease Analyzing Eye Images/Video)

      2. Deep learning based precise human body measurements from human image for reconstructive surgeries (Case Study: Craniofacial Measurements ( Facial Index and Nasal Index) for Facial Reconstructive Surgery. For this case study, we have collected data of population of Gujarat. In future, we aim to consider population of West India and then India)

      Thank you.

      • Sandhya Harikumar
        By Sandhya Harikumar  ~  1 month ago
        reply Reply

        What are the prerequisites to attend this session

        • Dr Mayuri Mehta
          By Dr Mayuri Mehta  ~  1 month ago
          reply Reply

          Hello Sandhya, 

          You should know the fundamentals of machine learning to attend this session. 


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