5G IN ACTION: SHORTER DIAGNOSIS

Where has 5G been deployed to shorten the time for diagnosis?

The Liverpool 5G Create project is using a private 5G network to deploy pressure ulcer management systems and urine monitoring systems in the community. This will result in faster diagnosis for patients and increased efficiency for the sector.

In the US, the Austin Cancer Center has deployed a high-speed 5G network to quickly and reliably transport huge data files from PET scans (typically up to 1 gigabyte of information per patient per study).

Austin cancer center

At the Samsung Medical Center in South Korea, typically tissue samples taken from patients during surgery are treated for analysis and sent back to pathologists in an adjacent room; this requires up to 20 minutes of walking back and forth, making it difficult for pathologists to conduct on-site group analyses. But the deployment of a 5G network, which offers ultra-high speeds and low latency, has enabled digital diagnostic pathology: doctors can now send 4 gigabyte frozen section biopsy images at an average speed of 1 gigabyte per second. This enables data to be easily and readily shared with colleagues in different departments and buildings, facilitating real-time feedback, more efficient working and faster diagnosis for critical patients.

The Chicago based Rush University Medical Center has taken a different approach, deploying sensors and ultra high definition cameras powered by 5G in patients’ hospital rooms to deliver “connected care”.  As a result, the hospital can continuously monitor patients and using AI, identify potential issues before they become emergencies — ensuring better patient outcomes. “We strongly believe 5G is a game-changing technology that when fully implemented will help us support better hospital operations as well as provide the highest quality patient and staff experience,” said Dr. Shafiq Rab, senior vice president and chief information officer, Rush University Medical Center and the Rush System for Health. 

5G-facilitated AI is likewise being used in the XiangNan University hospital in Hunan Province, China — quickly detecting and identifying pneumonic lesions, and providing quantitative assessment for diagnosis information. The system can pinpoint the disease in less than one minute, with a detection accuracy of 92 percent and a recall rate of 97 percent on test data sets. Such capabilities will play a vital role in assisting overstretched healthcare wards.  

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