![]() Faced with the difficulty of deciphering a wide variety of ID cards, Zocdoc’s engineering and data science teams were able to create a neural network proof-of-concept in just one day by using cloud-based GPU servers from AWS.Īfter extracting the member ID information, Insurance Checker then verifies the patient’s health coverage in real time, checks in-network benefits, and the estimated co-pay.Įven when patients understand their health plan coverage, there is often a mismatch between patients who wait weeks for appointments versus doctors who have more immediate openings. The system uses deep-learning-based computer vision to scan the ID card and extract the correct policy ID information. With Zocdoc’s Insurance Checker, a patient just has to take a photo of their health insurance card. Our search process uses multiple algorithms to parse a patient’s intent and match their needs to the right specialist,” says Serkan Kutan, CTO of Zocdoc. “As a consumer-facing tech company operating in healthcare, we are eager to bring data driven innovations to improve the patient experience. ![]() Patients can get appointments within 24 hours, compared to a national average wait time of 24 days for new patients. With algorithms built using the TensorFlow deep learning framework, Zocdoc matches patients and doctors more efficiently. Deep learning on AWS is at the core of Zocdoc’s mission to optimize health care data to help patients. Zocdoc helps patients navigate this maze, allowing individuals with health care needs to make more informed choices and find care that matches their needs. A recent survey showed that more than half of Americans have difficulty understanding their insurance coverage, and three-quarters want an easier way to check if doctors are in-network.
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