Identifying sleep apnea early “will undoubtedly reduce the occurrence of severe OSA and the progression of other illnesses related to untreated sleep disorders,” Kamalasan says. Somnoware is working on data warehousing solutions that will provide an integrated repository to process patient datasets by unifying information from sources including electronic medical record applications, sleep diagnostic devices, and CPAPs.
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Subath Kamalasan, CEO and co-founder of respiratory and sleep management software Somnoware, says AI will be “transformative” as it learns how to “identify who is most likely to develop OSA long before any symptoms are present.” And more closely by analogy replicates the kind of knowledge gained by experience.Įither way, “it makes it a lot more efficient,” says Fernandez.ĪI is also making screening and diagnosis more robust.
In this model, there are fewer assumptions by the team.
The second method, unsupervised learning, leaves it to the machine to interrogate the data itself. “We used algorithms similar to Netflix and Spotify-it’s the same personalization technology,” he says. What the machine learns from this data will help prove or disprove the hypothesis. In this model, researchers come up with a hypothesis and try it out by feeding the machine historic data, showing the machine what worked and what had mixed results. The first is through supervised learning. There are two ways machines can learn, says Fernandez. Unlike the super-intelligent machines of science fiction, a modern AI machine cannot be programmed to be smart. “What we’re most excited about in regard to AI is in treatment selection by making an easier, better, faster diagnosis,” he says, adding that this opens a path to more personalization and better therapy adherence. Smart Diagnosisįor Chris Fernandez, CEO of EnsoData, the makers of sleep scoring and analysis solution EnsoSleep, the two biggest challenges for sleep professionals are 1) under-diagnosis of OSA and 2) adherence to treatment. While a truly “thinking” machine may be many decades away, today’s AI-powered technologies are certainly smarter than the machines of even a few years ago and are poised to transform the diagnosis and treatment of sleep-disordered breathing. Clarke’s HAL 9000-and until recently they have been little more than the stuff of dreams.īut thanks to recent advancements in artificial intelligence (AI), a new class of machines is here to learn how to help people with obstructive sleep apnea (OSA) have pleasant dreams. Thinking machines have been the realms of scientific theory and fiction for more than 200 years-from mathematician Charles Babbage’s difference engine to author Arthur C.
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