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Search Results - heart+failure
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A Self-Assembled Implantable Microtubular Pacemaker for Wireless Cardiac Electrotherapy (Case No. 2024-059)
Summary: UCLA researchers in the Department of Bioengineering have developed a novel implantable microtubular pacemaker for reliable and comfortable pacing for patients with arrythmias. Background: Cardiac pacemakers are essential devices used to manage abnormal heart rhythms, or arrythmias, by sending electrical pulses to prompt the heart to beat...
Published: 9/13/2024
|
Inventor(s):
Tzung Hsiai
,
Shaolei Wang
Keywords(s):
arrhythmia
,
Cardiac Electrophysiology
,
cardiovascular monitoring
,
central venous pressure (CVP)
,
Continuous blood pressure monitoring
,
critical care
,
heart failure
,
hemodynamic monitoring
,
image signal processing
,
implantable sensors
,
medical device cardiac monitoring
,
non-invasive monitoring
,
pulmonary arterial pressure (PAP)
,
wearable
Category(s):
Medical Devices
,
Medical Devices > Monitoring And Recording Systems
,
Electrical
,
Electrical > Flexible Electronics
,
Medical Devices > Hospital Systems
,
Medical Devices > Cardiac
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
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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