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Search Results - deep-learning+analysis+algorithms
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Deep Neural Networks for Real-Time Non-invasive Continuous Peripheral Oxygen Saturation Monitoring (Case No. 2024-227)
Summary: UCLA researchers in the Department of Anesthesiology have developed a novel pulse oximetry methodology utilizing deep neural networks for non-invasive monitoring. Background: In the US alone, over 5 million patients are admitted to the ICU for oxygen saturation monitoring. They, as well as the more than 15 million patients undergoing surgery,...
Published: 7/26/2024
|
Inventor(s):
Sungsoo (Danny) Kim
,
Sohee Kwon
,
Mia Markey
,
Alan Bovik
,
Akos Rudas
,
Ravi Pal
,
Maxime Cannesson
Keywords(s):
Artifical Intelligence (Machine Learning, Data Mining)
,
Blood Pressure
,
cardiovascular monitoring
,
central venous pressure (CVP)
,
Continuous blood pressure monitoring
,
critical care
,
Deep learning-based sensing
,
deep-learning analysis algorithms
,
heart failure
,
hemodynamic monitoring
,
machine learning modeling
,
Monitoring (Medicine)
,
neural network
,
non-invasive monitoring
,
Oxygen
,
Oxygen Saturation
,
pulmonary arterial pressure (PAP)
,
Swan-Ganz catheter
Category(s):
Medical Devices > Monitoring And Recording Systems
,
Software & Algorithms > Digital Health
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
Securing Camera and Photography Systems From Deepfakes by Verifying Provenance and Reducing Attack Surfaces (Case No. 2024-270)
Summary: Researchers in the UCLA Department of Electrical and Computer Engineering have developed a multi-layer security framework to verify deepfake imagery data. Background: The exponential improvements in generative AI pose serious implication to the rise of synthetic media or “deepfakes”. Soon, deepfake images and videos will be...
Published: 9/27/2024
|
Inventor(s):
Alexander Vilesov
,
Achuta Kadambi
,
Yuan Tian
,
Nader Sehatbakhsh
Keywords(s):
AI image security
,
Artificial Intelligence
,
artificial intelligence algorithms
,
Artificial Neural Network
,
Artificial Neural Network Artificial Neuron
,
artificial-intelligent materials
,
attack surface reduction
,
data security
,
Deep Learning
,
Deep learning-based sensing
,
deep physical neural network
,
deepfake
,
deepfake protection
,
deep-learning analysis algorithms
,
deep-learning fake (deepfake)
,
generative artificial intelligence
,
image authenticity verification
,
image provenance
,
image signal processing
,
Medical artificial intelligence (AI)
,
social media
,
third-party verification
Category(s):
Software & Algorithms
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Software & Algorithms > Image Processing
,
Software & Algorithms > Security & Privacy
,
Electrical
,
Electrical > Visual Computing
,
Electrical > Visual Computing > Video Processing
Deep Learning-Enhanced Paper-Based Vertical Flow Assay for High-Sensitivity Troponin Detection Using Nanoparticle Amplification (Case No. 2024-179)
Summary: UCLA researchers from the Departments of Electrical and Computer Engineering and Bioengineering have developed a novel assay for point-of-care testing for acute myocardial infarction. Background: Cardiovascular diseases are responsible for a substantial number of deaths and economic burdens. Acute myocardial infarction (AMI) is an event...
Published: 11/13/2024
|
Inventor(s):
Aydogan Ozcan
,
Gyeo-Re Han
,
Artem Goncharov
,
Hyou-Arm Joung
,
Dino Di Carlo
Keywords(s):
acute myocardial infarction
,
Assay
,
Bioassay
,
biological assays
,
cardiometabolic disease
,
cardiopulmonary illness
,
Cardiovascular
,
Cardiovascular Disease
,
Cardiovascular Disease Nephropathy
,
cardiovascular diseases
,
cardiovascular modeling
,
cardiovascular prediction
,
cardiovascular therapeutic solution
,
deep-learning analysis algorithms
,
Flow Device
,
heart disease mitigation
,
high-sensitivity cardiac troponin I
,
Immunoassay
,
Laminar flow
,
nanoparticle amplification chemistry
,
point-of-care testing
,
Targets And Assays
,
vertical flow assay
Category(s):
Medical Devices
,
Medical Devices > Monitoring And Recording Systems
,
Platforms
,
Platforms > Diagnostic Platform Technologies
,
Diagnostic Markers
,
Diagnostic Markers > Targets And Assays