Recent research demonstrates that artificial intelligence (AI) can detect COVID-19 in lung ultrasound images, similar to how facial recognition software identifies faces in a crowd. This advancement in AI-driven medical diagnostics holds promise for rapidly and accurately diagnosing patients with COVID-19 and other lung-related diseases.

The development of an automated detection tool aims to aid healthcare professionals, particularly in emergency situations with high patient loads, such as during the early stages of the pandemic. Additionally, there is potential for utilizing this technology in wearables to monitor conditions like congestive heart failure, which shares similarities with COVID-19 in terms of lung fluid overload. For instance, wearable ultrasound patches could track fluid buildup and provide alerts for medication adjustments or medical consultations.

The AI system examines lung ultrasound images to identify specific features called B-lines, which indicate inflammation in patients with lung complications. Initially, using AI to assess COVID-19 indicators in lung ultrasound images was challenging due to limited patient data and evolving understanding of the disease. The AI tool operates as a deep neural network, mimicking the interconnected neurons of the brain to recognize patterns and perform complex tasks.

Source: hub.jhu.edu

 

 

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