Forget WebMD. Kang is looking to take looking up medical symptoms and getting diagnosis recommendations to a new, more accurate level for patients and doctors
A new startup has emerged from the shadows with a respectable $3.3 million seed round with some heavy hitting investors leading the way: Bessemer Venture Partners, Comcast Ventures, Mangrove Capital, Lerer Hippeau Ventures, Primary Ventures, and Taboola CEO Adam Singolda who is joining their board.
The new company is headed by former Vroom and Wix CEO Allon Bloch. Their software takes an AI approach to diagnosing symptoms, that will at one time facilitate a conversation with a user about his or her symptoms while simultaneously drawing crowd-sourced data from others who reported similar symptoms. From there, Kang’s platform would draw diagnostic and treatment suggestions.
“After 9 years of personally never joining another board/advisory beyond Taboola, I’m excited to share I’m joining as a board member of a company in the Consumer Health Information space that I believe will drive a revolution, and can help a lot of people around the world,” wrote Singolda in a statement. “Searching online for medical pains is completely broken where searching for the most common pain always result with either you have cancer, or some other worse outcome. Horrible.”
His words seem to reflect a sort of “WebMD effect” if you will, where would-be patients often take their symptoms to indicate more serious conditions than a more comment ailment. Singolda compares this technology to SIRI or Alexa, which would set expectations high for Kang. While not the only medical information site associated with self-diagnosis, such sites might be in trouble. If searches for WebMD indexed by Google Trends are any indication, the site has seen a steady and steep decline in traffic.
Faith in a diagnosis-suggesting website or platform might be rekindled with more accurate results, which seems to be what investors are banking on with such a high seed round (not to mention Bloch’s experience).
Still, this is not a tool that would necessarily be targeting patients for use. Doctors have just as much to gain. The tool would be an extremely helpful asset for medical professionals, as such a resource could give doctors much quicker insights into a patient’s reported symptoms.
But the big questions about Kang will revolve around, firstly, where they would be pulling their initial data sets that informs its AI mechanism, namely if it would depend on information already supplied to Kang or already have access to other data sources. The system’s data would only be stronger were it to continue to collect symptom and diagnosis correlations from doctors, but how would it jump-start itself?
Secondly, the company’s NLP would have to extremely sophisticated in order to correctly identify the nuance that a user would use to communicate pain or health concerns to a doctor. There is no technology right now that can properly judge the difference between when a patient says rates his or her pain a “7” on a scale of 1-10, or a “9.” Doctors, who often ask such a simple question, are presumed to have the experience to correlate that sort of patient reporting with diagnosis of certain conditions, diseases, or injuries.
Based in New York, the company has 10 employees between NYC and Tel Aviv.