11 May 2021
Researchers used AI to identify which daily changing clinical parameters best predict intervention responses in critically ill COVID-19 patients.
The investigators used machine learning to predict which patients might get worse and not respond positively to being turned onto their front in intensive care units (ICUs) – a technique known as proning that is commonly used in this setting to improve oxygenation of the lungs.
This dynamic understanding is vitally important when trying to understand a new life-threatening disease and to know when and in whom each intervention works. Dr Brijesh Patel Department of Surgery and Cancer
While the AI model was used on a retrospective cohort of patient data collected during the pandemic’s first wave, the study demonstrates the ability of AI methods to predict patient outcomes using routine clinical information used by ICU medics.
Fly-through of Malet St in London based on LiDAR data
Researchers have developed the first LiDAR-based augmented reality head-up display for use in vehicles. Tests on a prototype version of the technology suggest that it could improve road safety by ‘seeing through’ objects to alert of potential hazards without distracting the driver.
The technology, developed by researchers from the University of Cambridge, the University of Oxford and University College London (UCL), is based on LiDAR (light detection and ranging), and uses LiDAR data to create ultra-high-definition holographic representations of road objects which are beamed directly to the driver’s eyes, instead of 2D windscreen projections used in most head-up displays.
3D holographic head-up display could improve road safety eurekalert.org - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from eurekalert.org Daily Mail and Mail on Sunday newspapers.