The Polish-based health tech startup Cardiomatics has announced a $3.2 million seed raise to expand the use of its electrocardiogram reading automation technology that is able to provide accurate medical readings with only 10 seconds worth of input through the ECG sensor.
The round includes participation from Central and Eastern European VC Kaya, Nina Capital, Nova Capital, and Innovation Nest who invested in this project for their unique value proposition as well as an additional $1 million non-equity grant from Poland’s National Centre for Research Development which will be used by Cardiomatics towards research into how artificial intelligence can further improve patient care on such cases, where it may not have been possible previously due to lack of accurate data points needed before making decisions based off those limited data points.
Cardiomatics is a healthcare startup that was founded in 2017 and sells cloud tools to speed up diagnosis for cardiologists, clinicians, and other healthcare professionals. Cardiomatics’ software can automate the detection of heart abnormalities with reports generated in minutes faster than even trained human specialists could work on ECGs scans themselves; it democratizes access to quality care by enabling large-scale diagnoses without necessarily requiring an expert’s input.
The AI tool has analyzed more than 3 million hours of ECG signals commercially to date, per the startup. The software is able to integrate with over 25 different devices and it touts its modern cloud interface as differentiation in comparison with legacy medical software.
Cardiomatics, a provider of artificial intelligence-based diagnostic solutions for cardiac arrhythmias in the US and Europe with headquarters in Bengaluru, India announced it has raised $7.1 million from Sequoia Capital to expand its business operations across markets.
Cardiomatics will use proceeds from this round on product development as well as expanding their reach into new territories where they see significant growth opportunities like the Asia Pacific and Latin America.
The company also plans on obtaining FDA certification so that physicians can rely more heavily upon AI diagnostics when treating patients diagnosed with heart conditions such as atrial fibrillation or ventricular tachycardia which may lead to sudden death if left untreated.
So why is this $3.2 million Seed investment from experienced VCs such a big deal for an investor like me? Simply because the market for Cardiomatics’s technology is huge and growing.
According to the company, “the healthcare industry alone spends around $440 billion each year on diagnostics and medical services, most of which involves complex tests and procedures carried out by medical specialists.
Even with the best equipment, doctors make mistakes that are often costly for patients – from lost time to incorrect diagnosis.”
Thanks to Cardiomatics’s technology, however, this is no longer the case as ECG readings can now be gathered at home or in remote locations without any problems and then uploaded to the Cloud, where artificial intelligence algorithms will conduct a thorough analysis of the results.
The expert system is capable of providing detailed reports which Cardiomatics claims are far more accurate than what a human doctor can offer when provided with X-rays, chemical records, or other lab tests.
Cardiomatics Founder and CEO Krzysztof Kokot said, “Our machine learning technology applies deep learning to the ECG. It analyzes four years of data plus two million healthy and sick patient records. We also have a patent-pending for artificial intelligence methods that can predict heart disease in patients.”
“Getting an early-stage investment from central European VCs for our first round was very important to us,” said Artur Rojek, CTO, and co-founder of Cardiomatics. “Our plan now is to commercialize our technology through a subscription model.”
Cardiomatics’s proprietary deep learning algorithm has been developed over the past three years by its team including Krzysztof Kokot (Founder and CEO), Artur Rojek (CTO), and Patryk Graf (software architect).
Rojek added, “Deep learning technology is currently transforming big data in many fields. The more data we feed the algorithm with, the better it will become at its task.”
The system works by obtaining a single-lead ECG reading from the patient: this is analyzed and compared with a database of similar readings to generate a summary report. On its own, the device weighs only 35 grams, so it can be worn on the body unnoticed. This means that health checks can be carried out as often as necessary – even without an accompanying doctor.