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Harry's guest is Dekel Gelbman, founding CEO of FDNA. The company uses a combination of computer vision, deep learning, and other artificial intelligence techniques to improve and accelerate diagnostics and therapeutics for children with rare diseases.

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Note: MoneyBall Medicine is produced for the ear and designed to be heard. If you are able, we strongly encourage you to listen to the audio, which includes emotion and emphasis that's not on the page. Transcripts are generated using a combination of speech recognition software and human transcribers and may contain errors. Please check the corresponding audio before quoting in print.

Transcript

Harry Glorikian: Welcome to the Moneyball medicine podcast…

I'm your host Harry Glorikian. This series is all about the data-driven transformation of the healthcare and life sciences landscape. Each episode we dive deep through one-on-one interviews with leaders in the new cost-conscious value-based healthcare economy. We look at the challenges and opportunities they're facing and their predictions for the years to come.

My guest for today is Dekel Gelbman, who is the founding CEO of FDNA. He leads the corporate and business strategy of an innovative digital health company that develops technologies and SAS platforms used by thousands of clinician’s researchers and lab sites locally in the clinical genomic space. The main mission of the company is to give hope to children with rare diseases and their families.

FDNA which was founded in 2011, uses a combination of computer vision, deep learning, and artificial intelligence to analyze patient symptoms, physical features and genomic data in combination with a network of thousands of genetics professionals worldwide. Then they drive scientific insights to improve and accelerate diagnostics and therapeutics impacting the lives of children with rare diseases.

Harry Glorikian: Dekel, welcome to the show, good to have you.

Dekel Gelbman: Thank you very much, it's a pleasure being here.

Harry Glorikian: Dekel, we've known each other almost since the day you showed up here in Boston deciding whether you would place yourselves here as a company. Tell me how this whole thing got started, because it's not exactly what you would consider a normal route into the world of diagnostics or using AI and machine learning, and it was quite a