Machine Learning & Cardiology

Machine Learning & Cardiology

Machine Learning & Cardiology Tech startup EKO is boasting of a new world to overtake traditional cardiologists.

EKO claims that their algorithm had a 93% accuracy for detecting a murmur in a heart sound wave vs 90% for traditional Cardiologists using a stethoscope.

EKO just collaborated with 3M and Astra Zeneca to offer their Cardiology TeleHealth products. Furthermore, they received a $65m funding earlier this year.

Furthermore the misdiagnosis of common cardiac events is 80% for internal medicine and family practice physicians. So you are taking a negative 80% to a positive 93%. Moreover, this is a huge potential leap for the ability of patients to receive low-cost healthcare. Especially one that has a 93% accuracy vs an 80% failure rate.

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Moreover, Mobile Heart Disease Monitoring is an industry that should have many more rivals to EKO in the future as this is a potentially gigantic market. Furthermore, according to Centers for Disease Control and Prevention, they estimate that in the United States about 2.7 million and 6.1 million people suffer from Atrial Fibrillation. In addition, this number should rise with the increase in geriatric population. Currently, the atrial fibrillation market is about $6 billion per year in the United States.

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Machine Learning & Cardiology

About EkoEko, a cardiopulmonary digital health company, is elevating the way clinicians detect and monitor cardiac and respiratory disease by bringing together advanced sensors, patient and provider software, and AI-powered analysis. Its FDA-cleared platform is used by tens of thousands of clinicians. Treating millions of patients around the world, in-person and through telehealth.

In conclusion, the company is headquartered in Oakland, California. With investments from Highland Capital Partners, Questa Capital, Artis Ventures,NTTVC, DigiTx Partners, Mayo Clinic, Sutter Health, and others.

Machine Learning & Cardiology