iRhythm Technologies, Inc. (NASDAQ: IRTC), a leading digital health company focused on the advancement of cardiac care, announced the publication of a new study in the January 2019 edition of Nature Medicine showing expert-level detection of cardiac arrhythmias using a new deep learning, or artificial intelligence, approach for electrocardiogram (ECG) analysis across a variety of diagnostic classes. The findings come from a collaboration with the Stanford Machine Learning Group that has resulted in the development of a cutting-edge deep learning model capable of arrhythmia detection at a level comparable to a panel of expert cardiologists for a total of 12 output classes. The study is titled, Cardiologist-Level Arrhythmia Detection in Ambulatory Electrocardiograms with Deep Neural Networks.
The collaboration leveraged the iRhythm data science and clinical teams’ expertise in ECG analysis and the company’s proprietary and diversely labeled ECG data set to produce an arrhythmia detection algorithm delivering expert-level classification performance. To date, this is the only model published and shown to reliably detect and label 10 cardiac arrhythmias, as well as distinguish sinus rhythm and noise from artifact, for a total of 12 output classes, potentially giving clinicians a more comprehensive understanding of their patients’ heart rhythms. By applying these sophisticated algorithms to the vast amounts of data captured by continuous ECG monitors, this approach has the potential to increase the accuracy of physician diagnosis and improve the efficiency of expert-human ECG interpretation, so physicans can spend their limited time and resources focused on getting patients the right care.
"As powerful, deep learning algorithms become available for cardiac care, it’s important for the medical community to become more discerning about the overall quality of the algorithms that power the analytical tools we use", said Dr. Martin Maron, Director of the Hypertrophic Cardiomyopathy Center at Tufts Medical Center. "Not all algorithms perform equally and we need to educate ourselves on the sophistication and accuracy of those we rely on to drive our clinical decision-making. The results of iRhythm’s collaboration with Stanford is the first time an artificial intelligence model has been able to successfully detect and label these many arrhythmias, showing great promise for the future of arrhythmia diagnosis and care. An ongoing commitment to advancements in data analysis is critical to improving patient care."
The study results represent the significant effort to evaluate algorithm performance compared to a set of board-certified practicing cardiologists and referenced against a consensus committee of cardiology experts. The publication expands and validates the researchers’ previous findings around the performance of the algorithm, a 34-layer Deep Neural Network, which learned from 91,232 ECG records collected from 53,549 unique patients using the Zio by iRhythm ambulatory continuous cardiac monitoring device. This is the first time a model was developed across this number of arrhythmia classes with a data set of this size.
"Since our company’s inception we have been committed to advancing scientific discovery and methods that improve arrhythmia detection and analysis for better patient care. We are delighted that the Nature Medicine findings expand further our leadership in ECG analysis", said Kevin King, Chief Executive Officer of iRhythm Technologies, Inc. "We believe iRhythm’s state-of-the-art deep learning techniques, coupled with quality assurance by our human experts, will augment physicians’ ability to reach a confident diagnosis quickly and will be an important part of the future of health care delivery."
For more information on the study feel free to visit www.irhythmtech.com/ai.
During it's IPO debut, shares of San Fransisco based iRhythm Technologies rose by as much as 65% above their initial public offering price as the maker of a digital heart monitor made its debut as a publicly traded company on the Nasdaq. KLSC is exposed to iRhythm through its partner New Leaf Venture II LP.
In its first day of trading last Thursday the 20th of November, the stock rose as high as $28 before closing the session $26.05 (56% higher than the offer price) on volume of more than 23 million, raising the value of its IPO from an expected $86 million to $107 million. iRhythm is currently trading at $72.81 (a 280% increase on the debut price).
KLSC is working with its partner New Leaf Venture Partners to support their portfolio companies and to transfer the latest technologies to the Middle East and Noth Africa starting with KLSC's home market of Kuwait.
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About KLSC:
Kuwait Life Sciences (KLSC) was established in 2010, with a paid up capital of 18 million Kuwait Dinars (KD) which is equivalent to approximately $60 million US Dollars. KLSC is fully owned by National Technology Enterprises Company. National Technology Enterprises Company (NTEC) was incorporated in November of 2002, by the Kuwait Council of Ministers as a fully owned company by the Kuwait Investment Authority (KIA), the sovereign wealth fund of the State of Kuwait. Capitalized at 100 million Kuwait Dinars (KD) which is equivalent to approximately $350 million US Dollars, NTEC aims to play a vital role in servicing major stakeholders in Kuwait and the Middle East region with their technology requirements.
KLSC focuses on healthcare innovative concepts and demanded services which have a clear and unmet need in the Middle East and North Africa (MENA) region.KLSC has been designed as an integrated healthcare company building unique projects and is considered one of the pioneer venture capitalist and private equity companies in the Middle East that invests globally and operates regionally seeking to advance healthcare services and systems within the region. KLSC supports both public and private sector stakeholders to access emerging technologies, establish unique projects and adapt best practices prevailing in today’s healthcare field. KLSC operates in healthcare investment, life sciences training, medical technology and pharmaceutical distribution.
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