Deep learning algorithms identify patterns of COVID-19 in lung images and breath sounds. (Credit: EPFL)

New deep learning algorithms that identify patterns of COVID-19 in lung images and breath sounds may help in the fight against other respiratory diseases and the growing challenge of antibiotic resistance.

With data from ultrasound images and auscultation (chest/lung) sounds, the new algorithms can accurately diagnose the novel coronavirus in patients and predict how ill they are likely to become.

The deep learning algorithms are named DeepChest – using lung ultrasound images – and DeepBreath – using breath sounds from a digital stethoscope. This AI is helping to better understand complex patterns in these fundamental clinical exams. The researchers say the results are highly promising.

Expected to be released by the end of the year, DeepBreath should enable the diagnosis of COVID-19 from breath sounds. The researchers say that the first results suggest that DeepBreath is even able to detect asymptomatic COVID by identifying changes in lung tissue before the patient becomes aware of them.

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