[{"innerBlocks":[],"name":"core\/freeform","postId":1380,"blockType":{"name":"core\/freeform","keywords":[],"attributes":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"providesContext":[],"usesContext":[],"selectors":[],"supports":{"className":false,"customClassName":false,"reusable":false},"styles":[],"variations":[],"apiVersion":3,"title":"Classic","description":"Use the classic WordPress editor.","category":"text"},"originalContent":"Researchers at the Mayo Clinic have applied artificial intelligence to a routine method of measuring the heart\u2019s electrical activity to identify patients with asymptomatic left ventricular dysfunction.

According to Mayo officials, until now there hasn\u2019t been an inexpensive, noninvasive, painless screening tool for asymptomatic left ventricular dysfunction\u2014a precursor to heart failure\u2014available for diagnostic use.

However, they contend that an AI-enabled electrocardiogram (EKG) has proven to be a \u201cpowerful screening tool\u201d for individuals with ALVD, demonstrating accuracy on par with other common tests, such as prostate-specific antigen for prostate cancer, mammography for breast cancer and cervical cytology for cervical cancer.

Researchers trained a convolutional neural network to identify patients with asymptomatic left ventricular dysfunction using paired 12-lead EKG and echocardiogram data. What they found was that AI applied to a standard EKG reliably detects ALVD.

Results of their study<\/a> were published on Monday in the journal Nature Medicine.

Also See:<\/b> Mayo, Eko team on machine learning to detect heart abnormalities<\/a>

\u201cCongestive heart failure afflicts more than 5 million people and consumes more than $30 billion in healthcare expenditures in the U.S. alone,\u201d says Paul Friedman, MD, senior author and chair of the Midwest Department of Cardiovascular Medicine at Mayo Clinic. \u201cThe ability to acquire an ubiquitous, easily accessible, inexpensive recording in 10 seconds\u2014the EKG\u2014and to digitally process it with AI to extract new information about previously hidden heart disease holds great promise for saving lives and improving health.\u201d

Friedman also notes that for patients in the study without ventricular dysfunction, those with a positive AI screen were at four times the risk of developing future ventricular dysfunction, compared with those with a negative screen.

\u201cIn other words, the test not only identified asymptomatic disease, but also predicted risk of future disease, presumably by identifying very early, subtle EKG changes that occur before heart muscle weakness,\u201d he adds.","saveContent":"Researchers at the Mayo Clinic have applied artificial intelligence to a routine method of measuring the heart\u2019s electrical activity to identify patients with asymptomatic left ventricular dysfunction.

According to Mayo officials, until now there hasn\u2019t been an inexpensive, noninvasive, painless screening tool for asymptomatic left ventricular dysfunction\u2014a precursor to heart failure\u2014available for diagnostic use.

However, they contend that an AI-enabled electrocardiogram (EKG) has proven to be a \u201cpowerful screening tool\u201d for individuals with ALVD, demonstrating accuracy on par with other common tests, such as prostate-specific antigen for prostate cancer, mammography for breast cancer and cervical cytology for cervical cancer.

Researchers trained a convolutional neural network to identify patients with asymptomatic left ventricular dysfunction using paired 12-lead EKG and echocardiogram data. What they found was that AI applied to a standard EKG reliably detects ALVD.

Results of their study<\/a> were published on Monday in the journal Nature Medicine.

Also See:<\/b> Mayo, Eko team on machine learning to detect heart abnormalities<\/a>

\u201cCongestive heart failure afflicts more than 5 million people and consumes more than $30 billion in healthcare expenditures in the U.S. alone,\u201d says Paul Friedman, MD, senior author and chair of the Midwest Department of Cardiovascular Medicine at Mayo Clinic. \u201cThe ability to acquire an ubiquitous, easily accessible, inexpensive recording in 10 seconds\u2014the EKG\u2014and to digitally process it with AI to extract new information about previously hidden heart disease holds great promise for saving lives and improving health.\u201d

Friedman also notes that for patients in the study without ventricular dysfunction, those with a positive AI screen were at four times the risk of developing future ventricular dysfunction, compared with those with a negative screen.

\u201cIn other words, the test not only identified asymptomatic disease, but also predicted risk of future disease, presumably by identifying very early, subtle EKG changes that occur before heart muscle weakness,\u201d he adds.","order":0,"get_parent":{},"attributes":[],"attributesType":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"dynamicContent":""}]

AI-enabled EKG proves powerful screening tool for heart disease

More for you