Saudi Researchers Develop AI Model for Rapid and Accurate Sleep Apnea Detection

In a groundbreaking scientific initiative, Saudi researchers have developed an innovative artificial intelligence model designed to detect obstructive sleep apnea, a condition affecting over a billion people globally, using unidirectional electrocardiograms and advanced AI techniques.

A study led by Malak Al-Murshid at the University King Saud's Sleep Medicine and Research Center, published in the journal Frontiers in Artificial Intelligence, details how the model employs deep learning based on attention transformers, enabling faster and more accurate diagnoses compared to traditional testing methods.

The findings indicated that this new model outperformed previous studies by 13% in F1 score, with the ability to identify apnea cases with precision within a second. This advancement offers physicians precise and rapid diagnostic insights while significantly reducing costs compared to comprehensive polysomnography, which can take hours and requires manual analysis.

The model is notable for its use of a single biomarker, the electrocardiogram, coupled with intelligent spatial encoding via an autoencoder. This allows for the processing of raw data without the need for complex prior analysis, ensuring effectiveness even with noisy data.

This study reflects Saudi Arabia's ambition to invest in artificial intelligence to enhance the medical sector and lead the knowledge economy beyond oil, positioning the kingdom at the forefront of technological innovation both regionally and globally.