National University Hospital unveils spine AI
National University Hospital has introduced an AI tool to analyse lumbar spinal stenosis, a common indication for surgery among senior patients.
According to a media release, the tool called Spine AI automatically detects areas of narrowing of spinal canal and categorises them by severity. It was trained using more than 18,000 lumbar spine MRI images of 446 patients. In a study, the technology took as fast as “47 seconds” to analyse each spine.
Lumbar spinal stenosis is a condition in which the spinal canal narrows in the lower back and compresses the nerves and blood vessels supplying the lower limbs.
Currently being evaluated across the NUHS radiology department, Spine AI was developed by NUH, together with NUS School of Computing and the National University Spine Institute. Siemens Healthineers was also tapped to help optimise the AI’s user interface.
NUH is said to generate around 4,00 lumbar MRI scans each year. With Spine AI automating its analysis in seven minutes per scan on average, it could deliver 466 hours in time savings per year, estimates Dr Andrew Makmur, NUHS Group CTO and a consultant of the NUH Department of Diagnostic Imaging.
Korea to deploy AI to check on independent living seniors
The South Korean Ministry of Health and Welfare and the Comprehensive Support Center for the Elderly Living Alone will be utilising AI to connect with about 42,000 senior citizens expected to spend the upcoming Chuseok holidays alone.
Chuseok is a major autumn harvest festival in the Korean peninsula. In South Korea, it is celebrated for three days.
A part of the government’s personalised elderly care service, the AI Call service utilises text-to-speech and speech-to-text technology to make voice calls and collect and transmit call information.
Meanwhile, SK Telecom and Lotte Welfare Foundation have been tapped to provide technical assistance for the holiday call service.
Thai regional hospital trials CXR AI
Phrapokklao Hospital, a major regional hospital in Chanthaburi, a province south-west of Thailand’s capital Bangkok, has recently implemented a chest X-ray (CXR) analysis AI to augment community screening of lung cancer.
“In most Thai government hospitals, [CXRs] are interpreted by non-radiologists. However, in community hospitals, there are often no radiologists available to read CXRs at all. By overlaying specialist AI to read all cases, we can support clinicians in detecting incidental high-risk nodules that may lead to lung cancer,” Dr Passakorn Wanchaijiraboon, deputy director of Phrapokklao Hospital’s Cancer Centre of Excellence, was quoted as saying. He led a recent evaluation study of the CXR solution qXR by the Indian company Qure.ai.
“The implementation of CXR AI is particularly beneficial in the context of community hospitals, where it can significantly enhance diagnostic capabilities in the absence of on-site radiologists,” Dr Wanchaijiraboon, who is also an oncologist, added.
Early this year, Qure.ai received the US Food and Drug Administration approval for the lung nodule on the qXR range of CXR analysis solutions.
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