Revolutionizing
heart care using
artificial intelligence
Providing clinicians and patients seamless access to
AI diagnostics for the electrocardiogram.
Impact
Our diagnostic software platform is aimed at revolutionizing heart care by providing clinicians worldwide with seamless access to AI diagnostics for electrocardiograms (ECGs). We are committed to keeping the healthcare system affordable and sustainable by timely diagnosis of heart disease using reliable ECG diagnostics close to patients.
Timely and more accurate detection of heart disease
The AI-powered software platform for electrocardiogram analysis developed by Cordys Analytics offers a new and innovative solution for healthcare professionals to detect heart disease earlier and more accurately. By harnessing the power of advanced deep learning techniques, this software enhances the diagnostic process by identifying subtle patterns and abnormalities in electrocardiogram data that might not be easily discernible through traditional methods. The software provides valuable new insights and supports healthcare professionals in making informed decisions.
A sustainable healthcare system
By enabling early detection, prevention, and more efficient diagnosis, AI-powered ECG software has the potential to reduce overall healthcare costs by minimising hospitalizations and complications associated with untreated heart conditions. With the software from Cordys Analytics, doctors and other healthcare professionals can detect heart disease earlier and more effectively, preventing unnecessary casualties and high treatment costs in the healthcare system, while improving the quality of life for patients with a heart condition.
AI algorithms integrated in clinician's workflow
Our software's vendor-agnostic nature allows it to seamlessly connect various healthcare organisations and ECG devices, making it a versatile tool for healthcare professionals working in different clinical settings and regions around the world. Its cloud-based architecture provides operational benefits, such as real-time data analysis, remote accessibility and scalability.
Connecting human and artificial intelligence in cardiology
Clinical Evidence
Through research projects with collaborators around the world, we have shown the value of ECG-based AI to improve patient outcomes.
News
Cordys Analytics Awarded Prestigious Health Holland TKI and EU IHI 7 Grants
September 12, 2024
What an incredible summer it's been! After learning in June that we were awarded the Eurostars grant of €800,000 with our partners UMC Utrecht and MedicalCSE, we received more great news: Cordys will receive funding from Health Holland and the EU. Cordys is set to receive €650,000 in funding to advance and refine its AI-driven platform for early heart disease detection using ECG technology.
Cordys Analytics Awarded Prestigious Eurostars Grant for AI-Powered Cardiovascular Diagnostics Project
June 4, 2024 — Funding
Cordys Analytics is proud to announce that it has been awarded a prestigious Eurostars grant. This grant, aimed at fostering innovation and collaboration among small and medium-sized enterprises across Europe, will significantly enhance Cordys Analytics' research and development capabilities.
Announcing Seed Funding Round
October 3, 2023 — Funding
UMC Utrecht spin-out Cordys Analytics secures investment for further development of AI-powered software platform for early and improved detection of heart disease
Cordys announces long-term research collaboration with the University Medical Center Utrecht
July 24, 2023 — Collaboration
The University Medical Center Utrecht (UMCU) and Cordys Analytics have entered into a long-term collaboration agreement.
Health Holland PPS grant received for developing heart attack algorithm
June 30, 2023 — Research Grant
University Medical Center Utrecht together with Cordys Analytics, and Meander Medical Center received Health Holland Public Private Partnership grant to develop and validate AI based identification of occlusive myocardial infarction using the ECG
Cordys Analytics moves to a new office at start-up incubator UtrechtInc
January 1, 2023 — General
Cordys Analytics has moved to a new office at start-up incubator UtrechtInc, a global Top 10 university start-up incubator for early-stage, scalable technology start-ups in the areas of health, sustainability, education, and artificial intelligence.
ZonMw Take-off grant received
June 1, 2022 — Research Grant
UMCU cardiology AI research team received ZonMw TakeOff grant
About Us
Cordys Analytics is a spin-out company that originates from the University Medical Center Utrecht. It focuses on using AI-powered algorithms to detect heart disease from electrocardiograms (ECGs).
Our research activities began in 2018 at the University Medical Center Utrecht (UMCU) in the Netherlands by René van Es, associate professor in the cardiology department, and Rutger van de Leur, a medical doctor and PhD student. The primary goal of our research was to develop AI-powered algorithms for the detection of heart disease from 12-lead electrocardiograms (ECGs). We collaborated with the UMCU's cardiovascular group to create top-notch machine learning algorithms. The UMCU provided a valuable resource of more than 1.5 million annotated ECGs. This dataset was used to train and validate machine learning algorithms, enabling the development of tools that outperformed the existing software in ECG devices.
In 2023 our team, which now included John van den Berg as CEO, successfully created and funded Cordys Analytics as a spin-out company. In the same year Cordys Analytics entered into a long-term collaboration agreement with the University Medical Center Utrecht, strengthening its ties with the institution where it originated.
The team at Cordys Analytics brings together clinicians, engineers and data scientists, enabling our company to drive innovation in the field of heart care. Cordys Analytics represents a successful example of translating academic research into practical applications with the potential to truly improve healthcare outcomes.
Our Team
John van den Berg has over 30 years of technology industry experience managing corporate development activities for companies like Dutch Railways, Nike, and Ziggo, leading high-performance teams in domestic and international markets. John is an experienced M&A executive and has been involved in dozens of acquisitions. Before taking on senior management roles, John was a management consultant with McKinsey. He holds degrees in pure mathematics and theoretical physics from Utrecht University and completed the accelerated INSEAD MBA.
René van Es has more than 10 years of experience in the development and validation of medical technology. René obtained his degree and PhD in Technical Medicine working on various medical devices to improve cardiac diagnostics and therapeutics and has hands on experience with the MDR process. Since 2021 René has been working as an Associated Professor at the department of Cardiology in the University Medical Center in Utrecht where he lead the cardiology AI research group. With this group, René was involved in the development and validation of Cordys' AI-algorithm portfolio.
Rutger van de Leur is a medical doctor and PhD candidate at the Department of Cardiology at the University Medical Center Utrecht. Rutger obtained his bachelor and master degree in both Medicine and Epidemiology at Utrecht University in 2020. During his internship he gained interest in automated analysis of ECGs using AI algorithms. His passion is to combine his medical, statistical and AI knowledge to be a bridge between the clinician and the AI technician. Currently, he focuses on state-of-the-art innovations for successful implementation of AI into clinical practice.
We are hiring
At Cordys Analytics we believe in hiring top talented people like you - ambitious, forward thinkers who love working in a healthtech start-up environment and who want to make a difference in the world and have an impact.
Feel like transforming heart care with us?
We are located in the vibrant UtrechtInc startup incubator. Drop by our office for a coffee, or click one of the buttons below.