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Search Results - artifical+intelligence+(machine+learning%2c+data+mining)
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Copyright: Large Language Models for Electronic Health Records (Case No. 2024-216)
Intro Sentence: UCLA researchers from the Department of Computational Medicine have developed a novel model for tabulating electronic health records. Background: Electronic Health Records (EHR) provide healthcare systems with insights into health histories. Machine learning models have been developed to use EHR for inference tasks based on specific...
Published: 9/6/2024
|
Inventor(s):
Jeffrey Chiang
,
Simon Lee
Keywords(s):
Artifical Intelligence (Machine Learning, Data Mining)
,
clinical decision support
,
EHR
,
EHR integration
,
electronic health records (EHR)
,
Hospital Systems And Devices
,
lab results analysis
,
large language model (LLNMs)
,
Machine Learning
,
machine learning modeling
,
patient questionnaire
,
personalized medicine
,
predictive analytics
,
specialist referral
Category(s):
Software & Algorithms
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Software & Algorithms > Data Analytics
,
Software & Algorithms > Programs
,
Medical Devices
,
Medical Devices > Hospital Systems
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
Object-Detecting Deep Learning for Multi-Event Electrochemical Data (Case No. 2024-088)
Summary: UCLA researchers in the Department of Chemistry and Biochemistry developed a custom-designed deep learning architecture for object detection and mechanisms classification to streamline the experimental design of cyclic voltammograms. Background: Cyclic voltammetry, a widely used electrochemical test, serves as a crucial tool in understanding...
Published: 8/23/2024
|
Inventor(s):
Chong Liu
,
Quanquan Gu
,
Benjamin Hoar
,
Weitong Zhang
,
Yuanzhou Chen
Keywords(s):
2D ultrasound imaging
,
Artifical Intelligence (Machine Learning, Data Mining)
,
artificial electromagnetic materials
,
bioelectronics
,
Biomaterial
,
electrochemical sensors
,
Electronics & Semiconductors
,
Lithium Battery
,
Lithium-Ion Battery
,
Machine Learning
,
Materials
,
Medical Devices and Materials
,
Medical diagnostics
,
Pharmaceutical Drug
,
Pharmaceutical testing
,
Rechargeable Battery
,
zzenergy storage
Category(s):
Electrical > Electronics & Semiconductors
,
Energy & Environment > Energy Efficiency
,
Energy & Environment > Energy Storage
,
Energy & Environment > Water Monitoring & Treatment
,
Software & Algorithms > Image Processing
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Electrical > Signal Processing
Full Spectrum Computer Vision for Photon Counting CT (Case No. 2024-058)
Summary: Researchers in the Department of Radiological Sciences have developed a machine learning algorithm that processes multispectral photon counting CT data for accurate medical imaging. Background: Photon counting computed tomography (PCCT) is a tremendous engineering advancement, enabling high resolution spectral imaging with myriad applications....
Published: 9/20/2024
|
Inventor(s):
Matthew Brown
,
Dieter Enzmann
,
John Hoffman
,
Michael Mcnitt-Gray
Keywords(s):
AI algorithms
,
Algorithm
,
Algorithm Optical Coherence Tomography
,
algorithmic cancer detection
,
Artifical Intelligence (Machine Learning, Data Mining)
,
artificial electromagnetic materials
,
Artificial Intelligence
,
artificial intelligence augmentation
,
Artificial Neural Network
,
Artificial Neural Network Artificial Neuron
,
artificial-intelligent materials
,
Big Data
,
Bladder Cancer
,
blood cancers
,
Brain cancer
,
Breast Cancer
,
Cancer
,
cancer antigen
,
cancer detection
,
Cancer Immunotherapy
,
Cancer stem cells
,
cancer target
,
Computed tomography
,
CT
,
Deep Learning
,
design software
,
Digital Pathology
,
generative artificial intelligence
,
Genetic Algorithm
,
Histopathological image analysis
,
Histopathology
,
histopathology images
,
hyperparameter optimization
,
Image Analysis
,
Image Processing
,
lympathic cancers
,
lymphatic cancer
,
Medical artificial intelligence (AI)
,
Mesenchymal Stem Cell Derived Cancer Cells
,
Orthotopic cancer models
,
Pancreatic cancer
,
pathology image analysis
,
Photon counting computed tomography (PCCT)
,
prostate cancer
,
Radiology
,
Radiology / Radiomitigation
,
Software
,
Software & Algorithms
,
Software Development Tools
,
Software-enabled learning
Category(s):
Software & Algorithms
,
Software & Algorithms > Image Processing
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Software & Algorithms > Data Analytics
Universal Linear Intensity Transformations Using Spatially-Incoherent Diffractive Processors (Case No. 2023-192)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel platform technology to facilitate the design of all-optical visual processors, which can be used to perform advanced computational tasks at the speed of light. Background: Information processing via light is a cutting-edge field among optics...
Published: 4/5/2024
|
Inventor(s):
Aydogan Ozcan
,
MD Sadman Rahman
,
Xilin Yang
Keywords(s):
Adaptive Optics
,
Algorithm Optical Coherence Tomography
,
all-optical diffractive computing
,
all-optical transformation
,
Artifical Intelligence (Machine Learning, Data Mining)
,
Artificial Intelligence
,
Atomic Force Microscopy Optical Tweezers
,
computational imaging
,
deep diffractive network
,
Deep Learning
,
Deep learning-based sensing
,
diffractive processor
,
Dispersion (Optics)
,
Electron Microscope
,
Electro-Optics
,
fluorescence microscopy
,
Focus (Optics)
,
Infrared Electromagnetic Spectrum Dispersion (Optics)
,
interference processor
,
large language model (LLNMs)
,
linear optics
,
linear transformations
,
Machine Learning
,
Microscope
,
Microscopy
,
Microscopy And Imaging
,
Near-Field Scanning Optical Microscope
,
neural networks
,
Nonlinear Optics
,
non-linear optics
,
Optical Coherence
,
Optical Communication
,
Optical computing
,
Optical Fiber Copper Wire And Cable
,
optical implementation
,
Optical Microscope
,
Optical networks
,
optical processor
,
optical transmission
,
Optics Parabolic Reflector Curved Mirror
,
phase-only diffractive network
,
reverse engineered optical system
,
Software
,
Software & Algorithms
,
Software Development Tools
,
spatially-incoherent light
,
start to end optics design
,
Surgical Instrument Optical Coherence Tomography
,
three dimensional imaging
,
visual computing
,
Waferscale Processors
Category(s):
Optics & Photonics
,
Optics & Photonics > Microscopy
,
Platforms
,
Software & Algorithms > Image Processing
,
Electrical
,
Electrical > Signal Processing
,
Electrical > Computing Hardware
A Programming Language to Execute Biological Experiments (Command Line Biology/Biowrapper) (Case No. 2024-049)
Intro Sentence: UCLA researchers in the Department of Molecular and Medical Pharmacology have developed a programming language to automate biological experiments. Background: Manual labor is a common bottleneck in biological sciences, with automation technology still being unobtainable and impractical for most scientists in biomedical research....
Published: 9/3/2024
|
Inventor(s):
Robert Damoiseaux
,
Michael Mellody
,
Ronan Bennett
,
Alejandro Huerta
,
Rutu Shah
Keywords(s):
Artifical Intelligence (Machine Learning, Data Mining)
,
Artificial Intelligence
,
artificial intelligence augmentation
,
Artificial Neural Network
,
artificial-intelligent materials
,
Automation
,
generative artificial intelligence
,
Machine Learning
,
machine learning modeling
,
Medical artificial intelligence (AI)
,
Programmable Logic Device
Category(s):
Software & Algorithms
,
Software & Algorithms > Data Analytics
,
Software & Algorithms > Programs
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Software & Algorithms > Image Processing
,
Life Science Research Tools
,
Life Science Research Tools > Research Methods
Synaptic Circuits Made From Transistors and Memory Capacitors (UCLA Case No. 2023-092)
Summary: UCLA researchers from the Department of Mechanical and Aerospace Engineering have developed a novel circuit architecture that emulates neural synapses for concurrent parallel computing. Background: Almost all modern computer chips consist of computing and learning processes that are implemented sequentially. To improve computing power,...
Published: 11/15/2024
|
Inventor(s):
Yong Chen
,
Zixuan Rong
Keywords(s):
Application-Specific Integrated Circuit
,
Artifical Intelligence (Machine Learning, Data Mining)
,
artificial electromagnetic materials
,
Artificial Intelligence
,
artificial intelligence augmentation
,
Artificial Neural Network
,
Artificial Neural Network Artificial Neuron
,
artificial-intelligent materials
,
autonomous control
,
computational efficiency
,
edge computing
,
Electronics & Semiconductors
,
Energy Efficiency
,
energy management
,
Integrated Circuit
,
Medical artificial intelligence (AI)
,
Neuromorphic circuits
,
parallel processing
,
parallel signal processing
,
processor design
,
Semiconductor
,
semiconductor chip foundries
,
Semiconductor Device
,
Semiconductors
,
synaptic resistor (synstor)
Category(s):
Electrical
,
Electrical > Electronics & Semiconductors
,
Electrical > Signal Processing
,
Materials
,
Materials > Semiconducting Materials
,
Software & Algorithms
,
Software & Algorithms > Artificial Intelligence & Machine Learning
Copyright: Machine Learning-Assisted Design of High Power Laser Systems (Case No. 2024-067)
Summary: UCLA Researchers from the Department of Electrical and Computer Engineering have developed a novel software leveraging advanced machine learning methods to simulate and design high-power laser systems. Background: High-power laser systems are crucial to many established industries and in cutting edge research. These systems can be used in...
Published: 1/8/2024
|
Inventor(s):
Sergio Carbajo Garcia
,
Jack Hirschman
,
Randy Lemons
Keywords(s):
Artifical Intelligence (Machine Learning, Data Mining)
,
Artificial Intelligence
,
artificial intelligence augmentation
,
Artificial Neural Network
,
artificial-intelligent materials
,
efficient laser design
,
Electronics & Semiconductors
,
Electro-Optics
,
high-powered laser systems
,
Laser
,
lasers
,
Lens (Optics)
,
linear optics
,
machine learning modeling
,
Medical artificial intelligence (AI)
,
non-linear optics
,
Optical Communication
,
Optical computing
,
optical implementation
,
Optics
,
parameter sweeping
,
Physics simulation
,
precision engraving
,
precision welding
,
reverse engineered optical system
,
Semiconductor
,
Semiconductor Device
,
Semiconductor Device Fabrication
,
start to end optics design
Category(s):
Software & Algorithms
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Electrical
,
Electrical > Instrumentation
,
Optics & Photonics
,
Optics & Photonics > Lasers
Copyright: Smart Histopathological Image Viewer With Guidance Generated by Artificial Intelligence (Case No. 2023-103)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed an AI-guided, smart histopathological image viewer to aid clinicians in the identification of regions of interest. Background: Digital pathology has transformed traditional glass histology slides into high-resolution digital slide images, priming the...
Published: 10/3/2024
|
Inventor(s):
Xiang Chen
,
Hongyan Gu
,
Mohammad Haeri
,
Shino Magaki
Keywords(s):
Artifical Intelligence (Machine Learning, Data Mining)
,
Artificial Neural Network
,
Clinical decision support system
,
Computer-Aided Diagnosis
,
Digital Health
,
Digital Pathology
,
Histopathological image analysis
,
Histopathology
,
histopathology images
,
Human-AI collaboration
,
Human-AI interaction
,
Medical artificial intelligence (AI)
,
Medical Imaging
,
pathology image analysis
Category(s):
Electrical
,
Electrical > Imaging
,
Medical Devices
,
Medical Devices > Medical Imaging
,
Software & Algorithms
,
Software & Algorithms > Digital Health
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Software & Algorithms > Image Processing
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