Sunday January 19, 2020

Artificial Intelligence (AI) can Detect Signs of Irregular Heart Rhythm

The research could improve the efficiency of the EKG, a noninvasive and widely available method of heart disease screening

0
//
Artificial Intelligence, Heart, Rhythm
The AI-enabled EKG can detect recent atrial fibrillation that occurred without symptoms or that is impending, potentially improving treatment options. Pixabay

Artificial Intelligence (AI) can detect the signs of an irregular heart rhythm — atrial fibrillation (AF) — in an electrocardiogram (EKG), even if the heart is in normal rhythm at the time of a test, says new Mayo Clinic research.

The AI-enabled EKG can detect recent atrial fibrillation that occurred without symptoms or that is impending, potentially improving treatment options.

The research could improve the efficiency of the EKG, a noninvasive and widely available method of heart disease screening, said the study published in The Lancet.

While common, atrial fibrillation often is fleeting and is challenging to diagnose.

Artificial Intelligence, Heart, Rhythm
Artificial Intelligence (AI) can detect the signs of an irregular heart rhythm — atrial fibrillation (AF) — in an electrocardiogram (EKG), even if the heart is in normal rhythm at the time of a test, says new Mayo Clinic research. Pixabay

“When people come in with a stroke, we really want to know if they had atrial fibrillation in the days before the stroke, because it guides the treatment,” said Paul Friedman, Chair of the Department of Cardiovascular Medicine at Mayo Clinic.

Blood thinners are very effective for preventing another stroke in people with atrial fibrillation.

“For those without atrial fibrillation, using blood thinners increases the risk of bleeding without substantial benefit. That’s important knowledge. We want to know if a patient has AF,” said Friedman.

Researchers tested AI on normal-rhythm EKGs from a group of 36,280 patients, of whom 3,051 were known to have atrial fibrillation. The AI-enabled EKG correctly identified the subtle patterns of atrial fibrillation with 90 per cent accuracy.

Also Read- Quarter of World’s Population at High Risk of Developing Tuberculosis

If proven out, AI-guided EKGs could direct the right treatment for disease caused by atrial fibrillation, even without symptoms.

Moreover, this technology can be processed using a smartphone or watch, making it readily available on a large scale. (IANS)

Next Story

Researchers Develop AI Tool To Detect Mental Health Issues

Tracking changes in clinical states is important to detect if there is a change that shows whether the condition has improved or worsened that would warrant the need for changing treatment

0
AI
The USC Signal Analysis and Interpretation Lab (SAIL), which has long applied artificial intelligence (AI) and machine learning to identify and classify video, audio and physiological data, partnered with researchers to analyse voice data from patients being treated for serious mental illnesses. Pixabay

Researchers, including one of Indian-origin, have developed an artificial intelligence (AI) tool that can accurately detect changes in clinical states in voice data of patients with bipolar, schizophrenia and depressive disorders as accurately as attending doctors.

“Machine learning allowed us to illuminate the various clinically-meaningful dimensions of language use and vocal patterns of the patients over time and personalised at each individual level,” said Indian-origin researcher and study senior author Shri Narayanan from University of Southern California (USC) in the US.

The USC Signal Analysis and Interpretation Lab (SAIL), which has long applied artificial intelligence and machine learning to identify and classify video, audio and physiological data, partnered with researchers to analyse voice data from patients being treated for serious mental illnesses.

For the results, the researchers used the ‘MyCoachConnect’ interactive voice and mobile tool, created and hosted on the Chorus platform to provide voice diaries related to their mental health states.

SAIL team then collaborated with researchers to apply artificial intelligence to listen to hundreds of voicemails using custom software to detect changes in patients’ clinical states. According to the study, the AI was able to match clinicians’ ratings of their patients.

Tracking changes in clinical states is important to detect if there is a change that shows whether the condition has improved or worsened that would warrant the need for changing treatment, the researchers said.

AI
Researchers, including one of Indian-origin, have developed an artificial intelligence (AI) tool that can accurately detect changes in clinical states in voice data of patients with bipolar, schizophrenia and depressive disorders as accurately as attending doctors. Pixabay

This project builds on SAIL’s body of work in behavioural machine intelligence to analyse psychotherapy sessions to detect empathy of addiction counselors-in-training in order to improve their chances of better outcomes, in addition to the Lab’s work analysing language for cognitive diagnoses and legal processes.

ALSO READ: Here’s How Fitbit Smartwatch May Help You Predict Flu in Real-Time

“Our approach builds on that fundamental technique to hear what people are saying about using the modern AI. We hope this will help us better understand how our patients are doing and transform mental health care to be more personalised and proactive to what an individual needs,” said study lead author Armen Arevian. (IANS)