From tagging people on social media to identifying travelers at ports of entry, facial recognition technology has become commonplace. Now, a young company is looking to save lives with it. More than 30 million Americans — 80 percent of them children — suffer from one of 7,000 rare genetic diseases. Many of these people bear abnormal growth patterns of the face or skull specific to their disease.
When it comes to identifying such diseases, however, the diagnosis process is surprisingly archaic. Doctors rely on a variety of antiquated approaches, from manually measuring the distances between facial features to drawing on decades of experience to detect patterns. On average, getting an accurate diagnosis takes seven years, after visiting multiple doctors.
Using NVIDIA’s CUDA parallel processing platform and cuDNN library, FDNA built a powerful network that supports apps for clinical evaluation and clinical consulting forums, as well as a medical library and an API. Together, these allow labs to use anonymous patient facial characteristics and phenotypes to increase the estimated 25 percent likelihood of finding diagnoses to 40 percent, Gelbman said.