A spinoff of the Medical University of Vienna (MUW), contextflow develops deep learning-based software to improve radiology workflows, saving radiologists time and improving reporting quality. Its core technology is a 3D image-based search engine (SEARCH), which detects disease patterns in 3D medical images like CTs and MRIs. It is currently being utilized by radiologists on lung CTs, identifying 19 different patterns (including those related to COVID-19), making it the only clinical decision support system of its kind. Another unique feature of SEARCH is its transparency, meaning radiologists can easily see and understand why the algorithm provided a given result. Plus, it integrates directly into various PACS systems, providing reference cases based on visual disease pattern detection, statistics, and medical literature necessary for differential diagnosis.
Select partners: TU Wien, LUMC, Alma Medical Imaging, Alphatron Medical, Dedalus, Sectra Amplifier Integrator, Wellbeing Software, Elsevier, Boehringer Ingelheim, STATdx, Roche, Nvidia, Clinic Barcelona Hospital Universitari, Medizinische Universität Wien, Medizinische Universität Innsbruck, University of Cambridge, Universitätsklinikum Düsseldorf, Universitätsklinikum Freiburg, Universitatsmedizin Mainz, Universitätsklinikum Regensburg.
Last round 🔗 €6.7M
September 7, 2021.
September 7, 2021.
Select investors B&C Innovation Investments, APEX Ventures, Nina Capital, IST cube, Nova Capital Management, Peak Pride, Crista Galli Ventures
Key people 🧑🤝🧑
- Markus Holzer - Co-founder & CEO
- Georg Langs - Co-founder & Chief Scientist
- René Donner - Co-founder, Individual ML Contributor & Technical Advisor
- Allan Hanbury - Co-founder & Big Data Evangelist
- Marcell Zoltán Farkas - CFO
- Markus Krenn - Chief Product Officer
- Magdalena Kedwani - Chief Regulatory Officer
- Nilaykumar Patel - Chief Quality Officer
- Julie Sufana - CMO
- Marcel Wassink - Chief Commercial Officer
- Rui Zhang - Chief Medical Officer / Radiologist
- Expandable tech: Whereas many AI companies focus on very specific diseases and offer only black-box decision support systems, contextflow takes a general approach and develops software that can be extended to additional modalities and organs. This makes contextflow the broadest AI software in the radiology field worldwide.
- It works: The study, in collaboration with the Medizinische Universität Wien and Universitätsklinikum AKH Wien shows reading time decreased by 31% when contextflow SEARCH Lung CT was available for use. 🔗
- Instant insights: contextflow delivers quantitative and qualitative insights for ILD, COPD, lung cancer and even COVID-19 directly in the default viewer. 🔗
- It's integrated: contextflow develops the components necessary for deep integrations, so comprehensive chest CT insights are available to users directly in their native PACS viewer. No clickouts necessary. 🔗
- Quantitative profiling: contextflow can help doctors and pharmacists to create cohorts of similar patients based on image characteristics or predict risk outcomes or treatment responses. 🔗
Awards & Recognitions 🏆
- 2021 Tech Tour Health: Winner 🔗
- 2021 One of Austria's top startups 🔗
- 2021 Austrian Chamber of Commerce: Born Global Champion 🔗
- 2020 Forbes DACH: One of the top AI30 startups
- 2019 Central Eastern Startup Awards: Top HealthTech Company - Austria
- 2018 One of 19 startups to participate in the Philips HealthWorks accelerator program
- 2016 Most Promising Startup by the BCS Search Industry 🔗
- 2016 Digital Innovation Award by the Austrian Federal Ministry of Education, Science and Research
contextflow's tremendous expertise in developing deep learning tools for radiology workflows rooted in the team's profound understanding of the clinical environment has led to incredibly strong interest in the market and 10+ partnerships with international clinics and hospitals. We at APEX are thrilled to continue to support contextflow's team and vision of tackling the many global challenges suffered by overstrained healthcare systems and thereby improve patient outcomes.
— Andreas Riegler, General Partner at APEX Ventures 🔗
To us, contextflow is a great example for a digital health start-up with strong connections to Austrian technology research & knowledge. contextflow showcases how the use of data and artificial intelligence algorithms can provide a clear value-add in healthcare. Therefore, we are very excited to support the company in scaling its technology worldwide alongside a strong group of fellow Austrian Investors.
— Alexander Sommer-Fein, Managing Director at Peak Pride and its HPH Start-up Unit 🔗
At Dubrava University Hospital, we take pride in providing the best care possible to our patients. There are many AI radiology solutions, but we agreed to the proof of concept with contextflow because their solution provides real value, particularly for new residents.
— Boris Brkljacic, President of the European Society of Radiology
I really like the transparency of contextflow SEARCH as opposed to other black box AI solutions. It's designed to support my workflow while leaving the final decision up to me.
— Elmar Kotter, Vice Chair and Head of Imaging Informatics at the Department of Radiology at Freiburg University Medical Center
contextflow SEARCH Lung CT is one of the applications that certainly fits radiology's current needs and can simplify the analysis of complex lung pathology. With the right insights and technology, we can succeed in introducing AI in a very attractive way to radiology departments on a global scale.
— Erik Ranschaert, Former President of the European Society of Medical Imaging Informatics (EuSoMII), Radiologist at St. Nikolaus Hospital in Eupen
Last update: July 13, 2023
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