08. September.2021 -Austria-based contextflow, an AI in radiology startup announced that it raised a total of EUR 6.7 Million (USD 8 Million). This round was led by Peak Pride Management GmbH, HPH (Hans Peter Haselsteiner) Start-up Unit and current investor APEX Ventures with its “APEX Best in Class’ ‘ fund. It is one of Europe’s largest Series A healthtech investments this year.
The funds will be used towards European and US market entry, FDA approval and expansion of the company’s offerings to include new features and products for a wider range of organs and modalities.
The Series A round was concluded in two closings, the first was of EUR 4.7 Million Series A funding round. A second closing included an additional EUR 2 Million from the new co-investor. The first round was led by B&C Innovation Investments GmbH (BCII) and included participation from new co-investor TTIP Beteiligungs GmbH and current investors APEX Ventures, Crista Galli Ventures, IST cube, Nina Capital and Novacapital.
Words from the investors –
Andreas Riegler, General Partner at APEX Ventures, said –
“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”.
Alexander Sommer-Fein, Managing Director at Peak Pride and its HPH Start-up Unit, continues: “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.”
About contextflow –
contextflow is a spin-off of the Medical University of Vienna (MUW), supported by the Technical University of Vienna (TU) and European research project KHRESMOI. Founded by a team of AI and engineering experts in July 2016, the company received the BCS Search Industry Most Promising Startup Award 2016, the 2017 Digital Innovation Award by the Austrian Ministry of Education, Science & Research, and was selected as one of 19 startups out of 700+ applications for the 2018 Philips HealthWorks accelerator. The Central European Startup Awards awarded us Best Healthcare Startup 2019 – Austria, and Forbes DACH listed us as one of the top AI30 startups for 2020.
It 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. contextflow 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 contextflow‘s SEARCH is its transparency, meaning radiologists can easily see and understand why the algorithm provided a given result.
As CEO & Co-Founder Markus Holzer explains, “Many AI companies focus on very specific diseases and offer only black-box decision support systems. In contrast, 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. contextflow pays attention to a flexible, transparent and scalable technology architecture to be best prepared for further business development.”
For more extensive analysis and Market Intelligence reports feel free to approach us or visit our website: Venture Capital Market Intelligence Reports | VCBay.
We try our best to fact check and bring the best, well-researched and non-plagiarized content to you. Please let us know
-if there are any discrepancies in any of our published stories,
-how we can improve,
-what stories you would like us to cover and what information you are looking for, in the comments section below or through our contact form! We look forward to your feedback and thank you for stopping by!
[…] Next Article […]