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£ 5.640 Million

AI breakthrough improves diabetic treatment and aviation engines

A new artificial intelligence created by the University of Queensland could transform the way aeroplane engine wear-and-tear is monitored, as well as improving insulin dosing for diabetics.

The technology was developed by a team led by Dr Nigel Greenwood, an alumnus of the university and founder of Evolving Machine Intelligence (EMI), a platform focusing on showcasing latest machine learning and artificial intelligence (AI) breakthoughs in healthcare and aviation.

“We’ve been using our machine-learning technology to data mine the medical histories of diabetics and recommend insulin dosages,” Dr Greenwood said.

“Our technology can recommend the best insulin dosage to keep each patient’s blood glucose levels under control with unprecedented stability and safety.

“It will allow for better and more accurate treatment than we’ve ever seen.”

The team’s flagship software is called Artificial Pancreas and is designed to interrogate medical data to construct personalised diabetes models for people with type-1 diabetes, and then generate suggested insulin infusion control.

In order to apply his team’s discoveries to aviation turbine engines and their systems, Dr Greenwood worked with UQ mechanical engineer Dr Ingo Jahn.

Commenting on the collaboration, Dr Jahn said: “we’re able to use EMI’s breakthrough AI technology to predict aviation engine component degradation and plan services to improve performance.

“It allows us to evolve computational models of aviation engines as if they were organisms and the AI can explain explicitly what it thinks is happening inside the engine”, he added.

In December 2018, EMI was named as one of the top-10 teams in the world at the IBM Watson AI XPRIZE, a competition aimed at using AI to solve the world’s toughest challenges.

The competition will reach its final stages with three finalists participating in the grand prize competition on the TED2020 conference, with a prize pool of $7.1m (roughly £5.4m).

Image via stevepb on Pixnio.

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