Kaggle Grandmaster Talk: The use of Computer Vision and Deep Learning to enhance medical diagnostics
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The increase in datafication is central to innovation across healthcare and life sciences. They translate various data sets and use AI to help forecast patterns, accelerate critical decisions that save lives, build more effective programs and workflows, and leverage the democratization of care.
With the growing focus on digital transformation, preventive healthcare, and early intervention, one game-changer for healthcare organizations is the application of Computer Vision and Deep Learning. By processing and extracting value from 2-D and 3-D medical imaging, geo-spatial data, and metadata, this cutting-edge AI technology can help address critical challenges and empower Doctors and caregivers to make faster and more accurate decisions or diagnostics.
Register to learn with the Kaggle Grandmaster and Senior Data Scientist at H2O.ai, Philipp Singer, how Computer Vision can enhance medical diagnostics, what are the common pitfalls in this area and how to avoid them.
- Philipp shares a bit of his experience and background
- Overview and quick intro to AI visualizations
- Examples of real-world use cases in healthcare
- Tips and tricks – pitfalls to avoid, how to have success in an AI project in healthcare
Philipp Singer is a Senior Data Scientist at H2O.ai. He obtained a PhD in computer science with honors at the Technical University of Graz. Philipp is a Kaggle Competition Grandmaster and achieved the highest 1st rank on the global competition leaderboard. He is currently number 3 in the platform’s global ranking (there are 165,000 Kaggle users and 240 Grandmasters). Philipp is passionate about machine learning, deep learning, and many other data-science related fields.
Kaggle Grandmaster e cientista de dados sênior na H2O.ai