Building Deep Learning based Healthcare Application using TensorFlow
Machine learning and deep learning have been rapidly adopted in various spheres of medicine such as discovery of drug, disease diagnosis, Genomics, medical imaging and bioinformatics for translating biomedical data into improved human healthcare. Machine learning/deep learning based healthcare applications assist physicians to make faster, cheaper and more accurate diagnosis.
We have successfully developed three deep learning based healthcare applications and are currently working on three more healthcare related projects. In this workshop, we will discuss one healthcare application titled "Deep Learning based Craniofacial Distance Measurement for Facial Reconstructive Surgery" which is developed by us using TensorFlow. Craniofacial Distances play important role in providing information related to facial structure. They include measurements of head and face that are to be measured from image.They are used in facial reconstructive surgeries such as cephalometry, treatment planning of various malocclusions, and craniofacial anomalies, where reliable and accurate data are very important and cannot be compromised.
Our discussion on healthcare application will include precise problem statement, the major steps involved in the solution (deep learning based face detection, deep learning based facial landmarking and craniofacial distance measurement), data set collection, experimental analysis and challenges faced & overcame to achieve this success. Subsequently, we will provide hands-on exposure to implement this healthcare solution using TensorFlow. Finally, we will briefly discuss the possible extensions of our work and the future scope of research in healthcare sector.
Outline/Structure of the Workshop
- Significance of Deep Learning for Healthcare Solutions (10 mins)
- Discussion of Healthcare Application 'Deep Learning based Craniofacial Distance Measurement for Facial Reconstructive Surgery' (20 mins)
- Hands-on Healthcare Application (Deep Learning based Craniofacial Distance Measurement for Facial Reconstructive Surgery) using TensorFlow (50 mins)
- Future Research Directions (5 mins)
- Q & A (5 mins)
After attending this workshop, participants will be able to…
- Build deep learning models using TensorFlow.
- Develop machine learning/deep learning based healthcare solutions using TensorFlow.
Students, Faculty Members and Researchers from sectors such as Engineering and Technology, Medical and Industry, who are working in the area of machine learning/deep learning or wish to start building machine learning/deep learning based healthcare applications.
Prerequisites for Attendees
Familiarity with fundamentals of machine Learning and matrices.
schedule Submitted 2 months ago
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