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Diagnosing Rare Diseases with Selfies

James Radke
Published Online: Thursday, Apr 06, 2017
Face recognition software has been in the news a lot lately, including the recent findings from the NIH showing the use of facial recognition technology to help diagnose patients with 22q11.2 deletion syndrome (22q11.2 DS).
 
The technology used by the NIH, which was developed in the innovation institute at Children's National Health System, was also very accurate in diagnosing Down syndrome and new studies are underway to better recognize Noonan syndrome and Williams syndrome.
 
And while the NIH tackles each disease individually, the private sector is thinking bigger. Instead of recognizing 4 diseases, they are going after 2000 rare diseases.
 
Recently, FDNA announced they have updated their Face2Gene software so that it now has facial images of tens of thousands of patients for more than 2,000 different rare genetic diseases.

Face2Gene

Face2Gene extracts de-identified data from photos of a patient’s face and compares them to a database of hundreds of thousands of similar data points from real-world, diagnosed cases. The result is a list of comprehensive phenotypic and genetic information with associated syndromes that supports clinical evaluations, analysis and interpretation of genetic testing.
 
The company was co-founded by one of the persons who developed Facebook’s facial recognition software. Expanding that concept to medical conditions, FDNA hopes its platform can help clinicians accelerate the diagnostic process. The company also hopes the technology can help researchers study rare diseases and pharmaceutical companies develop new therapies.
 
Dekel Gelbman, CEO of FDNA, said “Now, more than ever, it’s up to companies like ours to continue this vital research to help identify new syndromes and treatments.” Gelbman added, “This achievement, in gathering image data associated with more than 2,000 rare genetic diseases from 129 countries, is just the start for FDNA. Our goal is to continue to improve precision medicine through facial analysis and artificial intelligence in our fight against rare disease.”
 
Gelbman believes that FDNA and Face2Gene are intently focused on making significant contributions to the rare disease field and believes that their technology will play an important part in realizing the full potential of precision medicine initiatives.
 
For more information, visit www.FDNA.com.
 
Image of young boy undergoing NIH’s facial recognition software analysis for a possible diagnosis of DiGeorge syndrome courtesy the NIH. Credit: Paul Kruszka, et al.
 


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