Cardiologs has earned Frost & Sullivan’s New Product Innovation Award. The cloud-based artificial intelligence (AI) solution was recognised for its ability to analyse ambulatory ECG recordings faster and more reliably than traditional software, enabling clinicians to provide accurate, timely, and cost-effective arrhythmia diagnosis.
A press release reports that Cardiologs was launched in North America in 2018 “where it has achieved rapid adoption of its solution in the US market and continues to on board new customers onto its service”. It adds that “tens of thousands” of patients have been diagnosed using the Cardiologs analysis solution, and that number is projected to increase dramatically as the company continues its expansion into additional European countries and market segments in 2020.
Megha Joshi, research analyst, Transformational Health, Frost & Sullivan, comments: “Cardiologs has pioneered the implementation of deep learning to increase ECG data analysis throughput and predictive capability, two key aspects that can reduce costs associated with providing quality healthcare. Increased throughput also means reduced patient waiting time, which is a major factor affecting utilisation of healthcare.”
According to the press release, Frost & Sullivan also lists that Cardiologs’ solution has the following benefits: increased throughput of ECG data analysis: improved efficiency of cardiology departments; increased number of patients that are screened for arrhythmias; quicker diagnosis in cases of atrial fibrillation and other life-threatening arrhythmias.
Yann Fleureau, co-founder and CEO of Cardiologs, comments: “Cardiovascular disease remains a leading cause of death worldwide. Our vision is to create a technology that can help democratise access to expert level healthcare, and eliminate the growing socioeconomic medical divide around the globe. As our innovative technology is more broadly adopted, Cardiologs can help improve clinical outcomes and decrease costs for treatment of cardiovascular disease on a global scale.”