AI model will differentiate COVID-19 from other respiratory diseases

Chinese researchers published a paper in the journal Nature Communications earlier this month proposing an artificial intelligence model that can help doctors quickly differentiate between COVID-19, influenza, and pneumonia with high accuracy.

Since the COVID-19 outbreak, numerous AI systems have been developed and used for frontline detection and diagnoses, such as analyzing chest X-rays and CT scans.

However, with flu season approaching, if COVID-19 and influenza were to break out together, causing the CT diagnosis workload to skyrocket, differentiating between the two respiratory illnesses would prove challenging for doctors.

A new AI model may provide the answer. Researchers from Tsinghua University and Wuhan-based Union Hospital, affiliated with the Huazhong University of Science and Technology, have developed and evaluated an AI system using a large dataset with more than 11,000 CT volumes from COVID-19, influenza, non-viral community-acquired pneumonia, and non-pneumonia.

According to the paper, CT volumes of COVID-19 patients were collected mainly from February to March at three hospitals in Wuhan, once the epicenter of the COVID-19 epidemic in China.

The AI model, known as a deep convolutional neural network-based system, turned detection experiences accumulated by experts into algorithms. Test results showed that it can differentiate four respiratory diseases, including COVID-19, influenza, and non-pneumonia, with an AUC of 97.8 percent, indicating a high degree of detection accuracy.

In further studies, the research team compared the diagnostic performance of this CT-based AI system with that of five radiologists, and results show that the performance of the system is greater than that of its human counterparts.