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Thursday / October 19.

Deep Learning & Triage Automation on Display at Boomtown Demo Day

BOULDER, Colo. – On Dec. 6th, Boomtown Accelerator showcased the cohort of seven companies that recently completed its intensive 12-week mentoring program. The high-energy event at the Boulder Theater brought entrepreneurs to the stage to present their ideas to a sold-out audience. Representing Boomtown’s Health-Tech Accelerator program were two companies focused on improving care coordination and population health efforts for health systems.

“These entrepreneurs have had great success in initial projects,” explained Tom Base, managing director of the Boomtown Health-Tech Accelerator. “We’re excited to work with them and make connections in the industry.”

Going Beyond the Symptom Checker

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Shad Geotsch, CEO and co-founder of Wellness Intel. [Credit: Jeffrey Donenfeld]

Online symptom checkers cross-reference patient health problems and health research to suggest possible diagnoses; however, a recent study showed they only got the accurate diagnosis 58% of the time. Wellness Intel wants to change this.

“We use an algorithm to triage patients based on their health profiles,” said Shad Geotsch, CEO and co-founder of Wellness Intel. “It then finds nearby institutions that can treat their symptoms and take their insurance.”

Wellness Intel then goes one step further, offering a provider-facing platform that allows triage nurses to connect patients with the correct internal resources in record time. During trials, Wellness Intel was able to triage patients 15 times faster and with 99% accuracy.  

With increasing competition in the market for consumer-facing health services, Wellness Intel’s provider-facing platform offers a more comprehensive approach to automating the triage process.

Improving Healthcare through Deep Learning Technology

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John Lucas, CEO and founder of Predictive ReCognition. [Credit: Jeffrey Donenfeld]

Predictive ReCognition brings the power of real-time data analytics to healthcare. Decision-makers and caregivers are able to drill down on risk factors based on patient demographics, diagnosis, procedure code, and medication, giving hospital systems the ability to identify patterns and adapt operations.

“There are a lot of contributing factors that drive patient outcomes,” explained John Lucas, the company’s founder and CEO. “By applying deep learning, Predictive ReCognition makes this information hyper actionable for health systems.”

With a vast knowledge of both data science and healthcare, the team at Predictive ReCognition is uniquely positioned to inform decision-makers of risk potential in real-time and allow health systems to reach population health goals. The team is tight lipped on upcoming partnership opportunities, but with the market for population health management expected to reach $31.9 billion by 2020, investors are sure to take note.

 

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