Using Tech & AI to Combat the Virus

Radiologists at University Hospitals (UH), Cleveland Medical Center, read dozens of images every day. The process takes several hours. GE Healthcare’s (GEHC) Critical Care Suite software acts as AI on board the AMX 240 mobile x-ray unit. Once a chest x-ray is taken, the mobile x-ray unit recognizes if a patient has a collapsed lung and flags the image for immediate reading to help the patient on the rapid path to treatment.

“Today, there are a multitude of AI algorithms being developed, but very few solutions are seamlessly integrated into actual clinical workflow. GEHC selected UH to be the first US pilot site because of their extensive research relationship and the use of progressive IT. Radiology teams are looking to integrate AI to improve workflow, and be the Center of Excellence for Cardiothoracic Care,” said Katelyn Nye, GM, Global Mobile Radiography & AI at GEHC.

The evaluation phase for the Critical Care Suite was completed last December, and the technology is now in daily clinical practice. The suite is flagging between seven to 15 collapsed lungs per day with the hospital. No one on the team could have predicted the onset of the COVID-19 pandemic, but now this technology is able to identify and prioritize cases where the lung is collapsed which is crucial as ICUs see an increase in patients during the COVID-19 crisis.

Not only are lungs affected by Covid-19 but the virus also affects the heart. This means that hospitals do not just need mechanical ventilators, but they also rely on using technologies such as Electrocardiograms (ECG) and Ultrasound.

Today ECG and ultrasound machines sport state-of-the-art software that can keep tabs on COVID-19’s assault on the heart. Today, clinicians are using state-of-the-art features on ultrasound machines such as GEHC’s which affords a sharper image because it is compact and is well suited to use in the ICU where many COVID-19 patients are treated.

Also, algorithms help clinicians help clinicians to quickly acquire high quality images with the laptop-sized machine before leaving the room. The machine can then automatically send the images into a central image repository which allows for remote analysis to be done elsewhere in the hospital.


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