With imagination, creativity and a little bit of help from Microsoft, 3 university students have discovered a way to identify and diagnose Huntington’s disease (HD) and other neurological disorders for less than $50.
Hrishikesh Suresh, Declan Goncalves and Zeqi Cui – also referred to as Team NeuroGate – will be competing in the Microsoft Imagine Cup finals on July 27 after sharing their work that helps recognize neurodegenerative disorders like HD and Parkinson’s disease. Suresh is a medical student studying neurology at McMaster University. Both Goncalves and Cui study software and computer engineering at the University of Waterloo.
If they win, the trio will be awarded $100,000 and provided with mentorship time from Microsoft CEO Satya Nadella.
By combining machine learning and artificial intelligence provided by Microsoft’s Azure platform, Microsoft Kinect motion data, and its Leap Motion device to develop a test, Team NeuroGate met at HackHarvard, a Harvard University event in October, and later placed first in the Imagine Cup’s Canadian finals in May.
“Through a serious of random events, we ended up making a team and created this neurogate prototype,” said Goncalves to the Waterloo Chronicle
. “See(ing) how well we worked together (and) the fact that we had really good team chemistry, we decided to work on it for the next eight months,” said Goncalves.
HD is a neurodegenerative disease and can be life-threatening. Involuntary, random and sudden, twisting, or chorea, are the primary symptoms, and patients experience a slew of mental health and cognitive problems. People with HD can suffer impaired nerve cells, which leads to deterioration in several areas of the brain.
Team NeuroGate believes that their creation has the potential to reshape how neurological diseases are diagnosed, meaning that patients will be treated earlier and able to lead productive lives with the necessary treatment. All 3 members agree that, even if they don’t take home the top prize at the upcoming event, they’re dedicated to the idea and are already conceptualizing the framework for a tech startup based around their creation.
The inspiration for the test was in due in part to Suresh’s experiences as a medical student. Suresh told the Waterloo Chorinicle that while he was working in a family practice, he became acutely aware that the medical system is too reliant on a specialist, even when a general practitioner is capable of making a diagnosis. By making machine-learning tools available, Suresh hopes that “maybe we can off-load the work from the specialist to the primary care level, so that people can get access to treatment faster and have a better quality of life.”
“This is our very first starting block,” said Suresh. “A lot of diseases cause abnormalities to motion. As we get more patients and more data, the more the system sees about the kinds of diseases and abnormalities out there, and the more it can identify and diagnose.”
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