Artificial Intelligence is changing the way we relate to technology and each other. From the proliferation of chatbots driven by AI to help you buy insurance to AI that helps you storyboard a film with the ideal plot twists to lure the right demographic in order to make the film a commercial success, AI continues to become a part of our lives. 

The next frontier, AI for data driven medicine.

Today’s healthcare consumer has become more engaged in their own medical treatment – from genome sequencing to building a personalized health profile from the data in our fitness/activity trackers. All of that big data is being collated and connected in order to create a more predictive view of our health or medical condition. Data driven medicine has the ability to not only improve the speed and accuracy of diagnosis for genetic diseases, but also unlock the possibility of personalized medical treatments.

A Swiss company, Sophia Genetics has created collective AI for data driven medicine called Sophia. Sophia can read and aggregate the genetic code of DNA and predict and diagnose genetic diseases such as cancer. Sophia also uses AI to combine that genome data with analysis, medical science and expert opinion to create a diagnosis which helps healthcare professionals personalize their patient’s treatment.

Sophia continuously analyzes the collected pool of DNA data sent to the company by 170 hospitals globally and in doing so, improves its own ability to detect and diagnose genomic conditions.

“Sophia will constantly examine the genomic data of thousands of patients in our network and gradually teach itself to not only identify genomic diseases but to become more accurate in its diagnosis. This is the first time we have introduced machine learning into our operation,” said Jurgi Camblong, CEO and co-founder of Sophia Genetics. “As it constantly learns, it will vastly improve the speed and precision with which we can identify potentially life-threatening diseases, and allow us to diagnose many times more patients than we were able to previously.

 

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Source: http://bit.ly/2abL7Zn