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Approach for Cognitive Healthcare Decision Support


  • IBM Watson Health Imaging signs multiyear OEM agreement to license MaxQ AI’s patient specific - point of care – cognitive decision support algorithms.
  • The first application to be made available is MaxQ AI’s A.I. based intracranial hemorrhage detection.
  • Go-To-Market will focus on the delivery of cognitive based clinical decision support tools to service the acute care marketplace through IBM Watson Health Imaging.

Tel Aviv, Israel – January 24, 2017 – IBM (NYSE: IBM) and MaxQ AI announced today a multi-year, go to market relationship to deliver MaxQ AI’s cognitive-based clinical decision support algorithms to the acute care marketplace. The initial application, to be distributed through IBM Watson Health Imaging’s platform is MaxQ AI’s intracranial hemorrhage detection algorithm.


This is an example, of IBM Watson Health bringing cognitive tools into the daily workflow of the emergency department to help physicians assess patients suspected of head trauma or stroke, and rule out the presence of a bleed in the brain. Utilizing sophisticated deep learning, machine vision, the ‘right’ data, and clinical insights, the MaxQ AI algorithm has the intelligence to automatically highlight regions of interest for consideration by the physician of the potential presence of cerebral bleed(s) without interrupting a physician’s current workflow.

“The opportunity to license our deep vision application to IBM Watson Health Imaging creates a unique value proposition in healthcare”, said Gene Saragnese, Chairman & CEO of MaxQ AI. “Engaging closely with IBM allows for a near-zero footprint implementation at a customer location delivering ‘Cognitive to the bedside’ where we believe the future of healthcare lies; in the physician’s ability to impact the point of patient care through the use of cognitive clinical decision imaging support to consider the entire patient and thereby reducing medical errors. At MaxQ AI, we believe improvements in the interpretation of data will lead to better decisions, better decisions will lead to better outcomes for patients and lower cost for healthcare. This is what drives us forward every day.“

“The implementation of cognitive-based computer vision and clinical decision support tools to medicine in general, and to the Emergency Department, in particular, has the potential to increase the speed, accuracy, and efficiency of patient management – ultimately reducing diagnostic errors and improving clinical outcomes,” said Dr. Michael Lev, Director of Emergency Radiology at Massachusetts General Hospital and Professor of Radiology at Harvard Medical School. “MaxQ AI is ideally positioned to leverage this technology, and their willingness to collaborate with industry partners reflects their awareness of, and sensitivity to, the complexities of patient assessment in the acute care setting. The Company’s first algorithms – CT detection of intracranial bleeds – represents the confluence of physician know-how and artificial intelligence clinical support.”

“At IBM Watson Health Imaging, we are bringing the power of cognitive computing to healthcare to expand the physician’s patient view so they have greater confidence in their diagnostic and treatment decisions for their patients,” said Anne LeGrand, General Manager, IBM Watson Health Imaging. “Our relationship with MaxQ AI will accelerate the delivery of additional decision support tools to the acute care marketplace and is part of the first wave of commercialized offerings, designed to reduce practice pattern variation.”

Both IBM and MaxQ AI have a common goal, to augment and assist the emergency room physician in their patient assessment, and never to replace them. Thereby, harnessing clinical understanding in conjunction with machine vision and deep learning to provide real-time artificial intelligence-based clinical decision support to physicians in the emergency room.

“MaxQ AI is pioneering the use of A.I. in the emergency room,” said Steve Tolle, VP, and Chief Strategy Officer, IBM Watson Health Imaging. “MaxQ AI’s acute care cognitive clinical decision support product roadmap is aligned with the needs within the marketplace, supplying clinical decision support tools to improve patient outcomes.”

According to the American Heart Association and American Stroke Association (AHA/ASA), stroke is the fourth leading cause of death and one of the top causes of preventable disability in the United States.

Affecting 4% of the U.S. adults, it is forecasted that by 2030, there will be approximately 3.4 million stroke victims annually in the U.S., costing the healthcare system $240 Billion on an annual basis.

To learn more, visit the IBM Watson Booth 1003 at HIMMS 2017.

About MaxQ AI

MaxQ AI utilizes advanced cognitive analytics and artificial intelligence to deliver real-time decision support tools to improve clinical outcomes in acute medical scenarios. The foundation of clinical discovery and value creation lies in the deep clinical understanding of how to utilize the right data (electronic medical record, medical imaging, and genomic data). The MaxQ AI team of artificial intelligence, machine learning, deep learning, and algorithmic experts along with its medical and scientific advisory boards are achieving breakthroughs in standards of cost and care. To learn more, please visit

About IBM Watson Health

Watson is the first commercially available cognitive computing capability representing a new era in computing. The system, delivered through the cloud, analyzes high volumes of data, understands complex questions posed in natural language, and proposes evidence-based answers. Watson continuously learns, gaining in value and knowledge over time, from previous interactions. In April 2015, the company launched IBM Watson Health and the Watson Health Cloud platform. The new unit will help improve the ability of doctors, researchers, and insurers to innovate by surfacing insights from the massive amount of personal health data being created and shared daily. The Watson Health Cloud will allow this information to be de-identified, shared, and combined with a dynamic and constantly growing aggregated view of clinical, research, and social health data. For more information on IBM Watson, visit For more information on IBM Watson Health, visit Check out the IBM Watson press kit. Join the conversation at #ibmwatson and #watsonhealth. Follow Watson on Facebook and see Watson on YouTube and Flickr.