02 Jun 2020 - {{hitsCtrl.values.hits}}
Assists doctors distinguish between early, advanced and severe stages of pandemic
Leading ICT solutions provider Huawei has further extended the support to Sri Lanka’s fight against the COVID-19 pandemic via launching the AI-assisted automatic and quick diagnosis technology platform to frontline medical professionals.
This AI-assisted system empowered by Huawei’s Cloud technology deployed
at the
Colombo North Teaching Hospital in Ragama, integrating with the existing Picture Archiving and Communication System (PACS) will automatically, quickly and accurately output CT quantification results to imaging and clinical doctors.
This is further alleviating the shortage of imaging doctors, who can accurately diagnose COVID-19, relieving the pressures of quarantines and reducing the heavy workloads of doctors in Sri Lanka, who are working tirelessly to fight against COVID-19.
According to the solution, Huawei Cloud leverages the computer vision and medical image analysis technologies to segment the multiple pulmonary ground glass opacities (GGOs) and lung consolidation and make quantitative evaluations through CTs of patients’ lungs.
It combines clinical information and laboratory results to help doctors more accurately distinguish between early, advanced and severe stages of COVID-19, facilitating early screening and
prevention/control.
For confirmed cases in hospitals, this AI-assisted service can perform registration and quantitative analysis on the 3D dynamic data of multiple rechecks within a short period of time, helping doctors effectively evaluate patients’ conditions and drug use effects.
In recent times, Huawei Cloud has been working with various industries to carry out multiple AI-based scientific research projects on COVID-19.
Huawei has also joined hands with countries like Sri Lanka, Indonesia, Malaysia, Thailand, Bangladesh and others to address on-ground communication challenges, ensuring connectivity and supporting the essential services with innovative technologies during the COVID-19 pandemic.
17 Nov 2024 44 minute ago
17 Nov 2024 3 hours ago
17 Nov 2024 3 hours ago
17 Nov 2024 3 hours ago
17 Nov 2024 5 hours ago