“The data in healthcare is vast, unstructured, and relatively sparse,” points out Robert Mehler, COO and CIO, MedyMatch. Today, many healthcare providers find it difficult to unlock the potential of data. “Especially, in the Emergency Room (ER), physicians need to access real-time information to help patients recover quickly,” adds Mehler. MedyMatch addresses the needs of healthcare providers and patients by utilizing deep vision, advanced cognitive analytics, and artificial intelligence to deliver real time decision support tools to improve clinical outcomes in acute medical scenarios. “We are trying to structure the unstructured data and solve the problems in this space using the new analytical tools,” says Mehler.
In Mehler’s view, many complications and diseases can have long-term impact on patients. For instance, a relative of the co-founders of MedyMatch suffered from cerebrovascular accident at a time when real-time decision support mechanisms were not accessible to the physician in the ER to quickly treat the patient. “The cerebrovascular accident or stroke is treatable only within the hours of the onset of stroke. If it is not treated, the patient will either die or be permanently disabled for life,” says Mehler. This whole situation prompted a team of technologists to build a solution that produces better outcomes. “Our goal is to make every physician a life saving expert every time and to leverage data about patients to understand their needs and provide decision support tools on the course of treatment,” adds Mehler.
We are taking the fundamentals of cognitive analytics and applying it in the ER environment to improve clinical outcomes while reducing the cost of care
MedyMatch’s cloud-based platform receives medical images of a patient’s brain and analyzes them, according to regulatory and compliance practices to assess hemorrhage in the brain. The company uses machine learning, deep vision, and big data analysis to assess regions of interest for review. Each pixel in the image of a brain provides dynamic, metabolic information–the main context for disease. MedyMatch endeavors to unlock that context to drive better outcomes. “Patients sometimes are misdiagnosed which either leads to incorrect treatment or no treatment at all,” states Mehler. MedyMatch’s focus is to extract deep, actionable insights available in the images and engender quick assessments for the physicians enabling them to move their patients to the next steps of care. “We are taking the fundamentals of cognitive analytics and applying it in the ER environment to improve clinical outcomes while reducing the cost of care,” says Mehler.
The fact that MedyMatch is working in 3 Dimensional (3D) space sets it apart in the industry in terms of technology. The company uses data enrichment techniques that analyze sparse data in healthcare to allow deep vision and learning with less data in 3D space. The company is also working on a platform to consider 4D data as well.
In order to continue helping organizations select the right data, MedyMatch ties data scientists, machine learners, computer experts, and clinical developers together to enhance the quality of care. The company’s long term nextgeneration applications are also in the pipeline. “The new family of applications pending regulatory approval is under development in conjunction with our clinical partners,” says Mehler. MedyMatch will continue to build its applications that bring insights in front of the patients and allow them to receive better care.