18 August,2023 11:06 AM IST | New York | IANS
Image for representational purposes only. Photo Courtesy: iStock
A team of international scientists have developed a deep learning artificial intelligence model to screen for heart defect from birth. The model can screen electrocardiogram (ECG) for signs of atrial septal defects (ASD) -- a condition that can cause heart failure and is under-reported due to a lack of symptoms before irreversible complications arise.
While ECG, takes only about a minute to detect, when humans analyse an ECG readout for known abnormalities associated with ASD, there is limited sensitivity for picking up ASD. In the study, published in the journal eClinicalMedicine, the team fed a deep learning model ECG data from 80,947 patients in the US and Japan, over 18 who underwent both ECG and echocardiogram to detect ASD.
The model was more sensitive than using known abnormalities found on ECGs to screen for ASD. The model correctly detected ASD 93.7 per cent of the time, while using known abnormalities found ASD 80.6 per cent of the time. "It picked up much more than what an expert does using known abnormalities to identify cases of ASD," said Shinichi Goto, corresponding author and instructor in the Division of Cardiovascular Medicine at Brigham and Women's Hospital.
"If we can deploy our model on a population-level ECG screening, we would be able to pick up many more of these patients before they have irreversible damage," Goto added. ASD is a common congenital heart disease. It is caused by a hole in the heart's septum that lets blood flow between the left and right atriums.
ALSO READ
If you're positioned properly, it's an opportunity: Rahul shares views on AI
Apple Event 2024: New iPhone 16 set to lead AI revolution
Here's why Anil Kapoor is named on TIME's 100 most influential people in AI
New tech launch alert: Apple to launch iPhone 16 series on September 9
CARE Hospitals Bhubaneswar: Pioneering the Future of Healthcare with Artificial Intelligence and Robotics in Orthopedics
It's diagnosed in about 0.1 per cent to 0.2 per cent of the population but is likely underreported, Goto said. The symptoms of ASD are typically very mild, or in many cases, nonexistent until later in life. Symptoms include an inability to do strenuous exercise, affect the rate or rhythm of the heartbeat, heart palpitations, and an increased risk of pneumonia.
Even if ASD isn't causing symptoms, it can stress the heart and increase the risk of atrial fibrillation, stroke, heart failure, and pulmonary hypertension. At that point, the complications of ASD are irreversible, even if the defect is fixed later. If found early, ASD can be corrected with minimally invasive surgery to improve life expectancy and reduce complications.
The study results suggest that the technology could be used in population-level screening to detect ASD before it leads to irreversible heart damage. ECG is relatively low cost and currently performed in many contexts. "Perhaps this screening could be integrated into an annual PCP appointment or used to screen ECGs taken for other reasons," Goto said.
Also Read: Reduced grey matter in brain linked to teen smoking, nicotine addiction: Study
This story has been sourced from a third party syndicated feed, agencies. Mid-day accepts no responsibility or liability for its dependability, trustworthiness, reliability and data of the text. Mid-day management/mid-day.com reserves the sole right to alter, delete or remove (without notice) the content in its absolute discretion for any reason whatsoever