Tech Alliance of SWFL presents: AI-powered Healthcare

TALK 1: Simulating anatomically accurate motions for medical visualization using ML/AI

In this presentation, you will learn how Mesh Deformers, created with help of Machine Learning, bring high fidelity anatomical visualizations to Realtime Graphic Applications. We will cover the Unreal Neural Network Engine and the Machine Learning Deformer plugin. We will go over how these tools can be used to bring complex anatomical animations and simulations to real time applications that can allow you to interact with anatomy in motion without the need to make prerendered videos. We will also do a general overview of the solutions available in the industry and how they use Machine Learning in the healthcare field.

🗣️Speaker: Leonardo Guibert
Leonardo Guibert is a Supervisor of the Realtime Graphics Software Engineering team at Arthrex, a medical device company headquartered in Naples, FL. His work involves creating applications that show medical visualizations in realtime. Some examples include Arthroman, an interactable anatomical model and product browser showcasing different surgical implants and procedures.

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TALK 2: A novel Machine Learning approach to improving accuracy in the early prediction of heart failure
Let's build a tool to improve the accuracy of heart failure predictions! Watch Yogesh building and training a neural network model on a heart failure prediction dataset.

🗣️Speaker: Yogesh Seenichamy
Yogesh Seenichamy is a high school scholar with passion for machine learning which was sparked upon successfully implementing a neural network for movie recommendations. Since that moment, he has been advancing his understanding of machine learning methodologies.

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