Dedalus HealthCare integrates contextflow SEARCH Lung CT into DeepUnity

News Press

2021-11-02

“Artificial intelligence” is more than a buzzword, it offers medical professionals real added value for their work when intelligently integrated into the workflow. Patients in particular benefit from AI via safer diagnostics. Dedalus HealthCare is also noticing an increasing demand for solutions with AI and has already responded with some in-house developments. “At the same time, however, we are also looking at which of the existing solutions can add value to our portfolio,” says Marcus Muth, Head of Portfolio Management DIIT at Dedalus. For example, the company has partnered with contextflow, a leading provider of artificial intelligence for medical image analysis. “We began in September with a  cooperation in which we integrate the SEARCH Lung CT solution directly into the DeepUnity reporting workstation. When the radiologist reports a lung CT, they click a button and can seamlessly continue working with the tool. The results are then automatically transferred to the report,” says Muth, describing the process.

SEARCH Lung CT is a clinical decision support system that detects, visualizes and quantifies lung abnormalities and pulmonary nodules. “Specifically, it provides the location and extent of changes via heatmaps for six image patterns, as well as visualization and measurements of detected lung nodules. In addition, the tool analyzes and classifies 19 image patterns in selected regions, retrieves visually-similar, expert-verified reference cases, and provides relevant links to literature, guidelines, and differential diagnoses,” said Markus Krenn, Chief Product Officer at contextflow, explaining how the software works. A soon-to-be published study shows that average reading time is 31% shorter when contextflow SEARCH Lung CT is available for use. A trend towards improved diagnostic accuracy was also noted, and results hold for both junior and senior radiologists.

“We are pleased to have found an innovative and inspiring partner in contextflow. Its high-quality AI solution expands our portfolio and offers tangible added value to our users,” said Marcus Muth. “The integration works smoothly, and users can profitably apply the software to their diagnostics with just a few mouse clicks. We are looking forward to working with the market leader in the DACH market,” adds Markus Krenn.

The University Hospital of Freiburg and Vienna General Hospital are the first institutions to use the integrated solution.

About Dedalus:

Founded in Florence in 1982 by the current Executive Chairman Giorgio Moretti, Dedalus Group is one of the leading software providers for healthcare and diagnostics in Europe and worldwide. The shareholder structure guarantees stability and great financial strength mainly through the presence of Ardian, the largest private investment company in Europe and the fourth largest in the world. Since 2016, Dedalus has accelerated its expansion strategy, focusing on the growing demand for innovative and comprehensive information, communication and clinical transformation solutions. Today, Dedalus has a strong presence in Germany, Italy, France, the UK and Ireland, Northern Europe, Austria, Switzerland, Spain, China, Brazil, Australia, New Zealand and several locations in Latin America, the Middle East and Africa, giving it a presence in over 40 countries. Thanks to its undisputed top portfolio of leading-edge, latest-generation IT solutions, Dedalus covers the entire spectrum of healthcare operators, supporting more than 6,000 hospitals and 5,000 laboratories worldwide.

About contextflow:

contextflow is a spin-off of the Medical University of Vienna (MUW) supported by the Vienna University of Technology (TU) and the European research project KHRESMOI, whose goal was to develop a multimodal, multilingual search and recognition system for medical images and documents. Founded by a team of AI and engineering experts in July 2016, the company received the 2016 BCS Search Industry Most Promising Startup Award, the 2017 Digital Innovation Award from the Austrian Ministry of Education, Science & Research, and was selected as one of 19 startups out of over 700 applications for the 2018 Philips HealthWorks Accelerator. The Central European Startup Awards named contextflow Best Healthcare Startup 2019 – Austria, and Forbes DACH listed the company as one of the top AI30 startups for 2020.

Zebras & Unicorns Podcast mit CEO & Co-Founder Markus Holzer

News Press

2021-10-04

Kann eine KI jemals den Arzt ersetzen? In der neuesten Folge von Zebras & Unicorns plaudert Markus Holzer mit uns über das außergewöhnliche Series A Investment.

Wellbeing Software Partners with contextflow to Deliver Dynamic AI Clinical Decision Support to Radiologists

News Press

2021-09-15

contextflow’s software gives radiologists the agility to work effectively and efficiently

Vienna, Austria – September 15, 2021

Connected healthcare specialist Wellbeing Software has partnered with deep learning specialists contextflow to deliver their clinical decision support system to radiologists in the UK through Wellbeing Software’s AI Connect Marketplace. 

contextflow develops deep learning-based tools to help improve radiologists’ daily clinical workflows. The company’s core technology is a 3D image-based CDS system called contextflow SEARCH Lung CT, which is designed to help save time while increasing reporting quality and confidence. The software provides quantitative and qualitative image analysis results for 19 lung-specific  imaging patterns including nodule detection in chest CTs, providing relevant statistics, reference cases and differential diagnosis directly in your PACS.

contextflow CEO and Co-Founder Markus Holzer of contextflow says: “Our aim is to empower radiologists to complete their daily workload faster and with higher quality outcomes. Wellbeing Software’s expertise as a workflow and integration specialist will help us give clinicians the tools they need to blend clinical thinking and technological capabilities and create meaningful change to the way the radiologists work.”

Chris Yeowart, General Manager, Business Development at Wellbeing Software added: “At Wellbeing we are always looking for the most innovative companies to partner with. The work that contextflow has done improves the way in which radiologists are able to control their workflow and diagnose patients both quicker and more accurately and they’re a valuable asset to our AI Connect Marketplace.”

contextflow is the latest AI vendor to join the AI Connect Marketplace, having chosen to integrate their technology through Wellbeing Software’s AI Connect gateway, which allows hospitals to embed their chosen algorithms into their radiology workflow, no matter what RIS or PACS they’re running.

About Wellbeing Software

Wellbeing Software is a leading healthcare technology provider with a presence in more than 75% of NHS organisations. The company has combined its extensive UK resources and unparalleled experience in its specialist divisions – pathology, oncology, radiology, maternity, data management and electronic health records – uniting their core businesses to enable customers to build on existing investments in IT as a way of delivering connected healthcare records and better patient care.  

Wellbeing’s ability to connect its specialist systems with other third-party software enables healthcare organisations to achieve key objectives, such as paperless working and the creation of complete electronic health records. Through their established footprint, specialist knowledge and significant development resources, the company is building the foundations for connectivity within NHS organisations and beyond.

https://www.wellbeingsoftware.com

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.

contextflow Secures EUR 6.7 Million Series A Investment

News Press

2021-09-07

A second EUR 2 Million closing brings the Vienna-based AI in radiology startup contextflow’s total Series A investment to EUR 6.7 Million ($8 Million), 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.

Vienna, Austria – September 7, 2021

contextflow, a leading provider of artificial intelligence for medical image analysis, announces a EUR 6.7 Million Series A funding round. A second closing included an additional EUR 2 Million from new co-investor Peak Pride Management GmbH, HPH (Hans Peter Haselsteiner) Start-up Unit and current investor APEX Ventures with its “APEX Best in Class” fund. A first closing 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.

The closing represents one of the largest Series A healthtech investments in Europe this year to date. The funds will be used for accelerating market entry in Europe and the US, including obtaining FDA clearance for contextflow SEARCH Lung CT, as well as extending the company’s offerings to include new products and features covering a wider range of organs and modalities. 

Founded in 2016 as 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. 

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.”

contextflow secured previous investments from APEX Ventures, B&C Innovation Investments GmbH, Crista Galli Ventures, IST cube, Nina Capital and Novacapital. Now the company is joined by co-investor Peak Pride Management GmbH, HPH Start-up Unit as well as a follow-on fund from APEX Ventures titled “APEX Best in Class”.

“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”, says Andreas Riegler, General Partner at APEX Ventures. 

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.

contextflow Earns Coveted MDR Certificate for Medical Devices

News Press

2021-07-05

Fresh off its Series A funding round, the Austrian-based AI in radiology startup contextflow has announced it has received its MDR certificate for medical devices. The certificate allows the company to develop and place class IIa medical devices on the EU market. Deutsche Version hier. 

Vienna, Austria – June 23, 2021

contextflow, a leading provider of artificial intelligence for medical image analysis, announced it has received its Medical Device Regulation (MDR) certificate on June 7th, making it only one of 11 AI solutions to have secured this certification. Moreover, it is only one of 4 MDR-certified manufacturers to offer a solution for chest imaging at the moment.  

On May 26th, 2021, the new “Regulation (EU) 2017/745” came into force replacing the older “Medical Device Directive 93/42/EEC”. The new regulation is designed to make the EU legislative framework more robust while keeping in mind better protection of public health and patient safety. Not only is this new regulation aimed at facilitating patients’ access to devices in the European market in a very highly organised manner, but it also provides manufacturers comparatively detailed information on fulfilling the requirements, especially when it comes to safety and efficacy of medical devices.

“Having an MDR certificate signifies that the contextflow complies with the applicable regulatory requirements defined in the EU regulation 2017/745 on medical devices and allows the company to develop and market class IIa medical device software for radiology in the EU,” explains Nilaykumar Patel, Head of Quality Management. 

Only 20 notified bodies in the entire EU are allowed to certify medical device manufacturers, which has resulted in long waiting periods for manufacturer audits, particularly during the pandemic. contextflow began its certification process back in 2018.

Magdalena Kedwani, Head of Regulatory Affairs at contextflow continues, “This certification is key to EU market entry, and we’re very fortunate to be one of the first to have received it. We definitely could not have done this on our own and want to thank our consultant Martin Schmid from encotec who has supported us since 2019 in building a solid Quality Management System and preparing us for the MDR audit.”
contextflow’s core technology is SEARCH Lung CT, a 3D image-based search engine that detects disease patterns in 3D medical images like CTs and MRs. 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. With this certificate, SEARCH Lung CT is now officially ready to be sold in the EU, helping radiologists solve challenging cases.

Georg Langs übernimmt Professur für Machine Learning in Medical Imaging

News Press

2021-06-17

(Wien, 01-06-2021) Georg Langs hat mit Anfang Juni 2021 die Professur für Machine Learning in Medical Imaging angetreten. Langs leitet das Computational Imaging Research Lab an der Universitätsklinik für Radiologie und Nuklearmedizin der MedUni Wien.

Georg Langs hat an der Technischen Universität Wien Mathematik studiert, wo er einen Masterabschluss erwarb und 2007 erhielt er an der Technischen Universität Graz ein Doktorat in Informatik. Von 2007 bis 2008 war er Post-Doktorand am Labor für Angewandte Mathematik der Ecole Central de Paris und Mitglied der GALEN-Gruppe am INRIA Saclay, Ile-de-France. Von 2009 bis 2011 war er Research Scientist am Computer Science and Artificial Intelligence Lab am Massachusetts Institute of Technology, wo er weiterhin Research Affiliate bleibt und einen Teil des Jahres am MIT als Mitglied der Medical Vision Group verbringt.
An der Medizinischen Universität Wien leitet er das Computational Imaging Research Lab am Department für Biomedizinische Bildgebung und bildgeführte Therapie. Am 1. Juni wurde er zum Professor für Maschinelles Lernen in der medizinischen Bildgebung an der Medizinischen Universität Wien ernannt.

Maschinelles Lernen in der medizinischen Bildgebung
Maschinelles Lernen wird zu einem immer wichtigeren Bestandteil der Präzisionsmedizin. Es ist unerlässlich für die Vorhersage des individuellen Krankheitsverlaufs und des Ansprechens auf eine Behandlung auf der Grundlage umfangreicher Daten wie Bildgebung, Genomik, Anamnese oder klinischer Informationen.

„Es reicht nicht aus, maschinelles Lernen zur Automatisierung zu nutzen – das tun wir bereits. Der wichtigste Beitrag von maschinellem Lernen wird sein, uns zu helfen, etwas Neues zu entdecken: Das Vokabular der Muster zu erweitern, die zu Behandlungsentscheidungen führen oder uns neue Zusammenhänge aufzeigen.“

Georg Langs strebt an, die wissenschaftliche Arbeit im Bereich des maschinellen Lernens und der Präzisionsmedizin tiefgreifend zu integrieren, damit die daraus resultierenden Modelle nicht nur Vorhersagen treffen können, sondern uns Kenntnisse über die zugrunde liegenden Krankheits- und Reaktionsmechanismen liefern. Diese wachsende Rolle des maschinellen Lernens ist von entscheidender Bedeutung, da es Teil der Entwicklung neuer Behandlungen und der Entdeckung von Phänotypen wird, die maßgebend für Behandlungsentscheidungen sind.

„Fortschritt ist nur in interdisziplinären Forschungsteams möglich, die tagtäglich Fachwissen und Intuition in maschinellem Lernen, klinischer Bildgebung und Präzisionsmedizin zusammenbringen. Die Medizinische Universität Wien bietet dafür ein perfektes Umfeld“, sagt Langs.

contextflow announces mid-seven figures Series A Investment

News Press

2021-06-17

The Austrian-based AI in radiology startup contextflow secured a mid-seven figures Series A investment led by B&C Innovation Investments (BCII). 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.

Vienna, Austria – June 1, 2021

contextflow, a leading provider of artificial intelligence for medical image analysis, announced its first Series A financing round closing with a mid-seven figures investment led by B&C Innovation Investments GmbH with TTIP Beteiligungs GmbH as new Co-Investor and additional participation from current investors APEX Ventures, Crista Galli Ventures, IST cube, Nina Capital and Novacapital.

Founded in 2016 as 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 MRs. 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. 

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.”

The Series A funds will be used for accelerating market entry in Europe and the US, including obtaining FDA clearance for contextflow SEARCH Lung CT, and extending the company’s offerings to include new products and features covering a wider range of organs and modalities. 

contextflow has secured previous investments from APEX Ventures, Crista Galli Ventures, IST cube, Nina Capital and Novacapital, all of which contributed again to this first Series A closing. Now the company is joined by lead investor B&C Innovation Investments GmbH, whose focus is on investments in innovative technology-based growth companies.

“The use of artificial intelligence in healthcare is a rapidly growing field. contextflow offers a mature and reliable system that increases the efficiency of lung diagnosis for hospitals and radiologists in private practice and radiology institutes. In this way, valuable diagnostic support can be provided, which ultimately leads to faster and more accurate reporting as the basis for subsequent therapy. In addition to the added value of the product, the highly competent Austrian founding team is convincing, having already submitted the software to the U.S. medical device regulatory authority and having concrete growth plans,” says Thomas Zimpfer, Managing Director of B&C Innovation Investments.

This is the first closing announcement of contextflow’s Series A round. An additional time-limited second closing for selected investors will be finalized this summer.

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.