MedyMatch

Image on MedyMatch brain bleed decision support tool highlighting multiple areas on a patient scan where there might be bleeding
Gene Saragnese

CEO: Gene Saragnese
Based: Tel Aviv
Founded: 2013
Company website

The scoop

MedyMatch is working on artificial intelligence- and machine learning-based solutions to improve the quality and delivery of healthcare, with the ultimate goal of improving outcomes and driving down costs. And the company is starting in the emergency room.

Its first focus is bleeding in the brain. MedyMatch is developing tools that help physicians identify and quickly treat stroke or traumatic brain injury in acute settings.

A patient’s head CT scan is sent via the cloud to a processor, where MedyMatch’s software uses deep learning, patient data and clinical insights to indicate where there might be bleeding, CEO Gene Saragnese said previously.

“We know that many important decisions are made in acute care settings and in the emergency room, and that they have a big impact on lives and on the cost of care,” Saragnese said.

What makes MedyMatch fierce

Four months after it emerged from stealth in February 2016, MedyMatch teamed up with a New Jersey hospital to develop a real-time, decision-support tool for the diagnosis of stroke.

And in March this year, the company inked a pair of deals that would see Samsung and IBM Watson integrate its AI-based solution into their imaging offerings. The first deal would bring the technology to Samsung’s medical imaging machines in prehospital settings, such as ambulances.

The tech can differentiate between hemorrhagic stroke, caused when a weakened blood vessel ruptures, and an ischemic stroke, caused by a blockage in the blood vessel. It could help ambulance teams or ER staff quickly rule out bleeding in the brain and administer a drug to dissolve the clot behind an ischemic stroke.

What sets MedyMatch’s platform apart is that it “unlocks the full richness of 3D imaging in conjunction with other patient data,” Saragnese said. Other AI companies may look at just data from the electronic medical record, he said. Conversely, they may be focused on analyzing medical images to relieve the growing burden on radiologists, or to standardize the interpretation of imaging.

Historically, improving medical imaging has been about creating higher-resolution images, or producing them more quickly.

“But the future is not just going to be about making better images,” Saragnese said. “It’s going to be about giving better answers.” There has been a rise in more intelligent imaging systems that don’t just provide images but also help physicians understand the images.

“This is where we are focused as a company. It’s where we think we can make a difference for our patients,” he said.

What to look for

MedyMatch reeled in about $2 million in seed funding from angel investors and was at the tail end of a series A round at the time of writing. The company is actively seeking new strategic partners and in November, it unveiled another collaboration, this time with GE Healthcare. Saragnese expects to be in the market with at least one clinical application by the first quarter of next year.

MedyMatch