In part one of our series on analyzing Holter ECG signals, we address the challenge of accuracy and human error in manual analysis. Cardiomatics provides a solution by offering cloud-based AI technology that ensures precise interpretation of ECG signals, reducing reliance on human interpretation. Trusted by leading medical institutions and validated in clinical trials, Cardiomatics delivers accurate reports with a positive feedback rate of 99.9%. With AI algorithms constantly learning and improving, Cardiomatics enhances diagnostic precision and efficiency in clinical practice. Learn more about implementing Cardiomatics software in your workplace to streamline ECG analysis and improve patient care.
In the UK, the backlog of cardiovascular patients awaiting vital heart care is growing, worsened by challenges from the COVID-19 pandemic. With over 100,000 individuals waiting for treatment, AI algorithms offer a solution to reduce this backlog. Cardiomatics, a cloud-based AI software, streamlines ECG analysis, cutting analysis time by up to 80% and providing accurate reports in just four clicks. Trusted by leading institutions and validated in clinical trials, Cardiomatics helps doctors focus on patient care. Contact us to learn more about how AI can support managing the backlog of heart care in the UK.
Artificial intelligence (AI) is transforming cardiology by automating ECG signal analysis, addressing challenges worsened by cardiovascular diseases and the pandemic. Manual analysis of Holter monitor ECG tests is time-consuming and demands expertise, leading to a backlog in heart care. AI algorithms, like those in Cardiomatics software, analyze signals swiftly and accurately, reducing analysis time by up to 80%. With just four clicks, doctors receive reports for interpretation and treatment planning. PZU Zdrowie’s collaboration with Cardiomatics highlights the growing trust in AI solutions to enhance medical care.
Recent research underscores the importance of 7-day ECG monitoring for post-stroke patients to detect crucial arrhythmias and guide treatment. Dr. Ulrich Ingold from Interlaken Hospital praises its effectiveness in identifying atrial fibrillation (AF) and aiding treatment decisions. Utilizing Cardiomatics software streamlines analysis, reducing resource use and enhancing patient care. This innovative solution has garnered praise from medical professionals for its reliability and efficiency. Join the many GPs and cardiologists benefiting from Cardiomatics to enhance ECG analysis.
Unlocking the potential of AI in healthcare, Cardiomatics adheres to stringent quality standards and regulations, ensuring patient privacy and data security. Through meticulous data preparation and continuous model assessment, we pioneer the development and implementation of AI-based prediction models in cardiology. Join us in revolutionizing healthcare and explore career opportunities with our dynamic team!
During the pandemic, many medical professionals shifted to remote work, facing challenges accessing necessary tools located in hospitals and clinics. Recognizing this need, organizations like the AMA and AHA praised telemedicine as a powerful solution. Cloud-based technologies and telehealth services support remote work for physicians, facilitating tasks like patient monitoring.
Remote healthcare extends to patients as well, with telemedicine enabling remote diagnosis and monitoring. Cardiomatics offers a solution for cardiology, allowing doctors to analyze ECGs anytime, anywhere, with precision and efficiency.
With solutions like Cardiomatics, both healthcare workers and patients can access quality care remotely.
Cardiac resynchronization therapy (CRT) holds promise for heart failure patients, but not all respond equally. Collaborating with the Medical University of Warsaw, we developed an AI algorithm to detect ineffective CRT pacing, potentially improving patient care. Our study involving 541 patients showed high sensitivity and precision in identifying effective CRT stimulation. Published in the Journal of Cardiovascular Development and Disease, our findings offer promising implications for optimizing CRT settings and enhancing patient outcomes.
In the rapidly evolving field of cardiology, managing the influx of scientific literature and patient data is a growing challenge. Technology, including AI, offers solutions to sift through vast amounts of data, aiding clinicians in diagnosis and therapy decisions. Cardiomatics provides automated ECG analysis, leveraging millions of clinical cases to deliver precise insights quickly, ultimately saving clinicians valuable time and improving patient care. Explore how Cardiomatics technology is revolutionizing cardiac care in the age of AI.
Cameras and ECG machines share a similar trajectory of evolution from bulky, complex devices to compact, accessible tools. Just as mobile phones revolutionized photography, handheld ECG devices are becoming more ubiquitous, offering convenience and quality previously unavailable. AI and cloud technologies are poised to streamline data processing and analysis in both fields, bridging the gap between increasing data volume and limited expertise in healthcare.
Cardiomatics and the Medical University of Warsaw are collaborating to develop Cardiomatics Junior, an innovative tool for automatic assessment of ECG signals in children. By utilizing AI-based algorithms, this project aims to revolutionize paediatric cardiology diagnostics, potentially reducing analysis time to 5 minutes and improving accessibility to Holter monitor testing for young patients. Supported by the National Centre for Research and Development, this groundbreaking initiative will benefit physicians, Holter monitor manufacturers, and clinical trial implementers, ultimately enhancing diagnosis and treatment of paediatric heart conditions.
Medical-grade algorithms in cardiology, powered by AI, are revolutionizing diagnosis, workflow, and patient outcomes. By automating ECG analysis, AI saves valuable physician time and enhances precision in detecting cardiovascular conditions. This technology streamlines workflows, improves access to care, and ensures patient safety, marking a significant advancement in healthcare. With AI integration, hospitals can achieve higher cost-effectiveness without compromising quality, ushering in a new era of precision medicine.
Prof. Michael Kühne and Prof. Christine Meyer-Zürn are leading the SWISS-AF-Burden study at the University of Basel, investigating the impact of atrial fibrillation (AF) burden on cardiovascular incidents. Partnering with Cardiomatics, they aim to streamline research through AI-based ECG signal analysis. The study’s findings could influence future treatment recommendations, offering insights into personalized care approaches based on AF burden. Preliminary results are expected to reveal the association between AF burden and cardiovascular events, shaping more tailored patient management strategies.