May 10, 2021 11:02am In a study, the artificial intelligence screening tool significantly increased diagnoses of low ejection fraction in its earliest, most treatable stages without requiring a time-consuming echocardiogram. (Pixabay)
It still remains to be seen whether the sci-fi genre is correct and artificial intelligence will one day rise up against the human race, but in the meantime, AI just might save your life.
An algorithm developed by the Mayo Clinic can significantly increase the number of cases of low ejection fraction caught in its earliest stages, when it’s still most treatable, according to a study published this month in Nature Medicine.
May 10, 2021
An artificial intelligence (AI)-enabled ECG algorithm integrated into routine care can increase the diagnosis of low ejection fraction (EF), according to new randomized trial data.
“Because ECG is a low-cost test frequently performed for a variety of purposes, the algorithm could potentially improve early diagnosis and treatment in broad populations,” write Xiaoxi Yao, PhD (Mayo Clinic, Rochester, MN), and colleagues in their study published online last week in
Nature Medicine. The algorithm uses neural networks to predict a high likelihood of low EF, an often-missed predictor of adverse events, based on standard 12-lead electrocardiogram data.
But the success of the technology developed by the same team who recently published results on identifying long QT syndrome in a similar fashion is dependent on it actually being used by clinicians, Yao told TCTMD. Since a myriad of AI-based algorithms are created daily, and money and IT resources to be engaged, “we can
AI-guided Detection of Heart Disease in Routine Practice by Colleen Fleiss on May 9, 2021 at 11:41 AM
Artificial intelligence (AI) screening helps detect low ejection fraction using data from an EKG could improve the diagnosis of this condition in routine practice. Study findings are published in Nature Medicine.
Systolic low ejection fraction is defined as the heart s inability to contract strongly enough with each beat to pump at least 50% of the blood from its chamber. An echocardiogram can readily diagnose low ejection fraction, but this time-consuming imaging test requires more resources than a 12-lead EKG, which is fast, inexpensive and readily available. The AI-enabled EKG algorithm was tested and developed through a convolutional neural network and validated in subsequent studies.
Mayo Clinic shared results of a study showing that an AI tool developed by the system could be used to improve diagnosis of low ejection fraction, a type of heart disease. It's part of a broader push by Mayo Clinic to commercialize AI-based diagnostic tools, starting with spinout company Anumana.
New Study Demonstrates Value of AI-Enabled EKG Algorithm in Routine Practice
Written by AZoRoboticsMay 7 2021
There are several forms of heart disease, but some types of this medical condition, like asymptomatic low ejection fraction, can be difficult to detect, particularly during the early stages when therapies would be highly effective.
Image Credit: Mayo Clinic.
The EAGLE short for ECG AI-Guided Screening for Low Ejection Fraction trial attempted to establish whether an artificial intelligence (AI) screening tool designed to spot low ejection fraction through EKG data could enhance the diagnosis of this medical disorder in regular practice. The results of the study have been published in the