Search Results - algorithm-based+testing

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Intraoperative Deep Learning Model for Imputation of the Continuous Central Venous Pressure (CVP) and Pulmonary Arterial Pressure (PAP) Waveforms From (Case No. 2024-224)
Summary: Researchers in the UCLA Department of Anesthesiology have developed a deep learning model to accurately represent and visualize hemodynamic waveforms, or blood flow patterns, with minimally invasive approaches. Background: Swan-Ganz (SG) catheters are used for precise cardiac hemodynamic evaluations. Indicated for patients with severe...
Published: 9/3/2024   |   Inventor(s): Maxime Cannesson, Sungsoo (Danny) Kim, Akos Rudas, Jeffrey Chiang, Ravi Pal
Keywords(s): active learning, Algorithm, algorithm-based testing, arterial blood pressure (ABP), Artifical Intelligence (Machine Learning, Data Mining), artificial intelligence algorithms, blood cancers, blood flow management, Blood Pressure, Blood Proteins, cardiovascular monitoring, catheter, Catheterization, central venous pressure (CVP), Computer Aided Learning, Continuous blood pressure monitoring, critical care, curriculum learning, Deep Learning, Deep learning-based sensing, deep-learning analysis algorithms, heart failure, hemodynamic monitoring, Machine Learning, non-invasive monitoring, Perceptual Learning, pulmonary arterial pressure (PAP), Software & Algorithms, Swan-Ganz catheter
Category(s): Software & Algorithms, Software & Algorithms > Digital Health, Software & Algorithms > Artificial Intelligence & Machine Learning, Medical Devices, Medical Devices > Monitoring And Recording Systems
2023-021 A Ferrobotic Swarm Technology for Accessible, Adaptable, and Automated Testing
Summary: UCLA Researchers in the Department of Electrical and Computer Engineering have developed an automated, algorithm-driven nucleic acid amplification test (NAAT) method that is easy to manufacture, distribute, and yields accurate results with reduced demand of testing reagents. Background: Major epidemics over the last two decades have emerged...
Published: 8/8/2023   |   Inventor(s): Dino Di Carlo, Sam Emaminejad, Haisong Lin, Wenzhuo Yu, Kiarash AmirMozafariSabet
Keywords(s): Algorithm, algorithm-based testing, automated testing, Automation, Cell Counting/Imaging, COVID-19, Ferrofluid, ferrorobotics, high throughput testing, Nanotechnology, nucleic acid amplification test (NAAT), Nucleic Acid Platform Systems, Nucleic Acids, polymerase chain reaction (PCR), pooling, Software & Algorithms, viral testing
Category(s): Software & Algorithms, Life Science Research Tools, Life Science Research Tools > Research Methods, Electrical > Electronics & Semiconductors, Diagnostic Markers, Life Science Research Tools > Cell Counting And Imaging, Platforms > Diagnostic Platform Technologies