Automated Left Ventricular Ejection Fraction Assessment Using Deep Learning

This Omdena Local Chapter Challenge runs for 8 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world.

You will work on solving a local problem, initiated by the Topeka, USA Chapter.

The problem

Echocardiography is critical in cardiology. However, the full promise of echocardiography for precision medicine has been constrained by the requirement for human interpretation. In addition, the sonographer’s experience is crucial for the human evaluation of heart function, and despite their years of training, there remains inter-observer variability. Echocardiograms have a complex multi-view format, which contributes to the fact that deep learning, a new method for image analysis, has not yet been widely used to analyze them.  An artificial intelligence (AI) solution can help identify cardiac structures with accuracy and automate LVEF measurement and myocardial motion with confidence.

The goals

The project’s primary purpose is to accurately predict LVEF measurement.

With a duration of 4-weeks, this project aims to:

• Data Collection and Exploratory Data Analysis
• Preprocessing
• Feature Extraction
• Model Development and Training
• Evaluate Model

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.

A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work