With increasing workloads, radiologists face a choice between longer working hours or spending less time evaluating images. About 20% of cases require additional research from many sources – each one requiring up to 20 minutes with questionable success rates.
Vienna-based contextflow is a spin-off of the Medical University of Vienna supported by the Technical University of Vienna, and puts AI-based image recognition technology to improve outcomes in radiology.
When additional information is needed for reliably diagnosing a difficult oncological case, contextflow’s software searches for visually-similar reference cases. The company works closely together with radiologists to continually improve its solution.
The startup has now secured a financing round led by with APEX Ventures together with two new international investors: Crista Galli Ventures and Nina Capital.
“We are excited to have invested in contextflow and look forward to working together to shape the future of medical imaging,” said radiologist Dr. Fiona Pathiraja, founder and managing partner of Crista Galli Ventures.
“Contextflow was born in response to important challenges in modern radiology: radiologists today deal with an increasing amount of data, fine-grained disease variants that are the key for effective treatment decisions, and an ever-increasing workload,” said Marta-Gaia Zanchi, founder and managing partner of Nina Capital. “Contextflow has addressed this problem by finding a way to support radiologists during the process of image interpretation without disrupting their routine workflow in order to drastically reduce the time required for accurate diagnosis. For us, this company has it all: a thoughtful and ambitious team, a compelling and timely need, a deep-tech solution designed in response to this need that leverages a large and credible data asset, and a business model built on top of a very sophisticated understanding of how the system works.”
Using contextflow, radiologists can simply marks a region of interest in a scan (currently the company is working with lung CTs), and the software retrieves reference cases from other patients based on visual disease pattern detection. The system also provides medical literature helpful for differential diagnosis, all within seconds.
“There’s no more need for time-consuming and frustrating searches in different websites and books to find the information you need. It’s now just a mouse click away,” added Markus Holzer, co-founder and CEO of contextflow.
Contextflow plans to use the new capital to obtain a CE certification and accelerate the international proof of concepts (POCs). Currently, POCs with seven clinics in Germany, Austria, the Netherlands and Croatia are underway before scaling to other international markets in the coming year.
Founded in July 2016 by a team of KI and software development experts, the company received the ‘Most Promising Startup’ award in 2016 by the BCS Search Industry and received the Digital Innovation Award of the Austrian Federal Ministry of Education, Science and Research in 2017. In 2018, contextflow was selected as one of 19 startups out of over 700 applications to participate in the Philips HealthWorks accelerator program. Most recently it won Best Healthtech Startup – Austria from the Central European Startup Awards. It is currently testing its 3D image search with seven international partner hospitals and clinics.
Startups
via https://aiupnow.com
contact@bcurdy.com, Khareem Sudlow
