StuffThatWorks, which harnesses the power of artificial intelligence to crowdsource data on health-related issues, today announced it’s launching its platform after raising $9 million in seed funding.

When it comes to chronic conditions, many people find themselves dissatisfied with the slow process of medical science because it often requires lengthy test series and long visits with specialists. The properly cautious nature of medical treatment can lead to slow improvement, which leads many patients to social media to seek out anecdotes from other sufferers to identify other options.

For many patients and researchers, this second process is often haphazard and fraught with difficulty. It also often leads to questionable conclusions by patients who cannot easily sift through the experiences of other people in forums, Facebook and other places to get a better grasp on their own treatment.

Using a proprietary AI framework and the crowdsourced experiences of thousands of patients, StuffThatWorks hopes to provide that platform that can take those experiences and provide actionable insights for medical professionals to help suffers of chronic conditions.

“People are the ones that hold in-depth knowledge about themselves, their condition, and the way treatments affect them, ” said Yael Elish, co-foounder and chief executive of StuffThatWorks. “Collecting this knowledge in an organized and structured way across is the only way to compare effectiveness in scale. And when that’s done across all chronic conditions it creates a gold mine of data that can dramatically advance and facilitate research to the benefit of both the patient and the medical community.”

The more contributors the better the system gets for any given chronic condition. Although the platform is constantly collecting data from patients, it does not start providing access until it has enough experience information to start forming insights.

Initially, with no or little data available, the community will focus on inviting more people to share experiences. with only 100 contributors for now, initial insights about the condition only include vital stats and outcomes: age of onset, symptoms, aggravating factors and treatments.

At several hundred data points, the AI starts to rank treatment effectiveness levels. Finally, with thousands of people, the system can attempt to surface the most effective treatments for subgroups with similar internally consistent symptoms and outcomes and for individuals.

The platform currently hosts 110 condition communities, with nearly 180,000 contributors sharing more than 10 million data points and 150,000 experience-based, content-rich pages. Much of the data was collected while the company remained in stealth mode.

StuffThatWorks claims that its approach is relevant for all chronic conditions from the common, such as diabetes and attention deficit hyperactivity disorder, but also for rare and even orphaned diseases that receive little attention. The platform enables sufferers of specific conditions to create their own subgroups within minutes and invite others to take a survey and contribute as well.

To streamline the platform and make it as effective as possible for its clientele, StuffThatWorks is collaborating with a limited number of researchers, medical organizations and patient advocacy groups on Patient Reported Outcome research.

To build its database on Hidradenitis Suppurativa, a painful skin condition that causes inflamed lumps, StuffThatWorks collaborated with an external researcher from Bellinson hospital to perform a cross-sectional study. The company used its system to describe the cohort and compared the effectiveness of treatments based on their internal AI-model within formal guidelines per the Journal of the American Academy of Dermatology. This study has not yet been published.

This seed funding round was joined by Bessemer Venture Partners, 83North and Ofek Ventures. The company expects to use the funding to expand its operations, hone its AI algorithm and enable more condition-based communities to gather further data, thus enhancing the insights the platform can provide.

Photo: Photopin