Deep Learning for Medical Image Analysis
Panel: Building a Successful Data Science & AI Team

Deep learning offers an exciting emerging opportunity to unlock insights from Medical Images. With over 90% of all healthcare data as medical images, this opens up huge potential for advancing the healthcare industry.

Come learn how you too can be part of this revolution.

Talk will cover use cases, special challenges and solutions for Deep Learning for Medical Image Analysis.

You will learn about:
- Use cases for Deep Learning in Medical Image Analysis
- Different DNN architectures used for Medical Image Analysis
- Special purpose compute / accelerators for Deep Learning (Cloud/On-prem/Super-Computers)
- How to parallelize your models for faster training of models and serving for inferenceing.
- Optimization techniques to get the best performance from your cluster (like Kubernetes/ Apache Mesos / Spark)
- How to build an efficient Data Pipeline for Medical Image Analysis using Deep Learning
- Resources to jump start your journey - like public data sets, common models used in Medical Image Analysis

 

Geeta Chauhan is a Consulting CTO at SVSG with 20+ years of experience building new products, leading diverse global teams, scaling and architecting complex distributed systems for companies ranging from nimble startups to Fortune 500s. These days you can find her in the hallways of AI startups building Deep Learning based platforms or tinkering in her garage to convert her electric car to run autonomously. Prior to this, she was the CTO of Data Platforms at Alcatel-Lucent and led the Advanced Technology incubator for Genesys Labs. She is passionate about sustainability and mentors’ startups at Clean Tech Open the largest clean technology accelerator in the world.