MSc ENTECH student wins the biggest Innovation prize in memory of Alfred Nobel

On Tuesday, the 13th of October, MSc ENTECH student Allen Ali Mohammadi (UppsalaUniversity) and Max MohammadhassanMohammadi(KTH) won the biggest Innovation prize of the year 2015 (SKAPA). It was awarded in Stockholm together with a diploma in memory of Alfred Nobel for their invention, Complex Disease Detector, also known as CAD Detector.

CAD Detector is a decision support tool. It helps screen and diagnose complex diseases such as cancer and heart diseases at a significantly earlier stage by using artificial intelligence together with visualizing the clinically relevant data.

The motivation for receiving this honor was mentioned to be a disruptive innovation in Medicine and Healthcare. Their innovation can have a great impact on global health while generating massive values in terms of increasing quality of life together with saving time and costs.

The specialization in innovation and entrepreneurship at ENTECH has played an important role in different stages of this project. I’m definitely going to continue working on this. In fact, I have already registered a limited company in Sweden recently in order to take our innovation to the market, says Mohammadi.

This is Mohammadi´s second award for the CAD Detector as he won “Best Inventor 2014” award in eHealth at the World’s Digital Health Forum for this invention. Another proof for that the support to our innovative students pay off.

The results were announced at Tessinska Palace in Stockholm and the award was presented by Chris Heister the Stockholm county council.

Congratulations Ali Mohammadi!

MSc ENTECH student Ali Mohammadinow at Uppsala University has won the biggest innovation prize in memory of Alfred Nobel – The SKAPA award. He won it together with Max MohammadhassanMohammadifor a ,Complex Disease Detector (CAD). It is a support tool that helps screen and diagnose complex diseases such as cancer and heart diseases at a significantly earlier stage by using artificial intelligence together with visualizing the clinically relevant data.