Updated August 21, 2017.
The Human Diagnosis Project might have the newfound support of the American Medical Association (AMA), but physicians are slightly more skeptical of the crowdsourced approach to medical care.
Several physicians expressed doubts about the initiative, which blends machine learning with crowdsourced information from specialists around the country, according to Axios. Ethan Weiss, a cardiologist and associate professor at the University of California San Francisco School of Medicine, told the website he was concerned the initiative would end up “spitting out garbage.”
“I'm not sure how you'd begin to demonstrate that it works or doesn't work,” he said.
The recent partnership with AMA and several medical boards gives the project more firepower as it's being considered for a $100 million grant from the MacArthur Foundation. A spokesperson for the Human Diagnosis Project told Axios the project is already being validated at several of the top medical schools, such as Harvard and Johns Hopkins.
Managing expectations for artificial intelligence has been an important debate as of late. Researchers at Stanford University recently urged the industry to temper its expectations for machine learning to “soften a subsequent crash into a trough of disillusionment.”
Still, the success of AI still relies on making health data more accessible and ensuring they are free of inherent bias. Informatics researchers have said crowdsourcing data is at least one way to do that.
After publication, Justin Hamilton, a spokesperson for the Human Diagnosis Project emailed FierceHealthcare arguing that "while the doctors quoted had general options on technology in medicine, few were familiar with Human Dx and how it works."
Jayanth Komareni, chair of the Human Diagnosis Project, also said a research team led by David Bates, M.D., senior vice president and chief information officer at Bigham and Women's Hospital has submitted research on the Human Diagnosis Project for publication.
"For over a year, we have been able to see that the collective intelligence of physicians solving cases together using Human Dx significantly outperforms the vast majority of individual physicians solving cases alone on the system," he said in an emailed statement. "Other exciting research results which we are already seeing from physicians collaborating in the system will be published in the coming years, and we already are in discussions with the leading collective intelligence and machine learning research groups at MIT to join this work."