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In-Situ Stochastic Computing in Memory (Case No. 2024-121)
Summary: Researchers in the UCLA Department of Electrical and Computer Engineering have developed a data-converter-free in-memory computing circuit that greatly reduces data processing latencies. Background: Low latency and low power computing circuitry is in high demand for artificial intelligence (AI) / machine learning (ML) applications. Compute...
Published: 11/19/2024
|
Inventor(s):
Sudhakar Pamarti
,
Jiyue Yang
Keywords(s):
Category(s):
Electrical
,
Electrical > Computing Hardware
,
Electrical > Electronics & Semiconductors
,
Software & Algorithms > Artificial Intelligence & Machine Learning
AI-Powered Technology for Safe and Smart Charging of Li-Ion Batteries (Case No. 2024-209)
Summary: Researchers in the UCLA Department of Chemical and Biomolecular Engineering have developed a new battery management system to improve lithium-ion battery lifetimes. Background: Lithium-ion (Li-ion) batteries are crucial for powering many modern devices, from smartphones to electric vehicles due to their high energy density, long life cycle,...
Published: 10/15/2024
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Inventor(s):
Yuzhang Li
,
Jiayi Yu
,
Aki Takahashi
Keywords(s):
Category(s):
Materials
,
Software & Algorithms
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Energy & Environment
,
Energy & Environment > Energy Storage
,
Energy & Environment > Energy Storage > Batteries
,
Electrical
,
Electrical > Sensors
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
Comprehensive and Individualized Menopause Care Delivery Protocol With Technological Decision Support Aid (Case No. 2024-193)
Summary: Researchers in the UCLA Department of Obstetrics and Gynecology have developed a new clinical decision support system for improved menopause care. Background: Each year, approximately 1.3 million women in the United States enter menopause. This is often accompanied by symptoms such as hot flashes, mood changes, and sleep issues. In addition,...
Published: 10/2/2024
|
Inventor(s):
Rajita Patil
,
Erica Oberman
,
Brittany Davis
,
Rhonda Voskuhl
,
Kathleen Van Dyk
,
Ravi Aysola
,
Louise Dixon De Silva
,
Karol Watson
,
Lua Jafari
,
Julie Bernthal
,
Rashmi Mullur
,
Albert Shieh
,
Elizabeth Ko
,
Katie Hu
,
Aashini Master
,
Kelly Mccann
,
Kelsey Collins
,
Katherine Unverferth
,
Tamara Grisales
,
Amy Rosenman
,
Andrea Rapkin
Keywords(s):
clinical care methodology
,
clinical decision support
,
EHR
,
EHR integration
,
electronic health records (EHR)
,
FemTech
,
femtech medical device
,
lab results analysis
,
medical bias reduction
,
Menopause
,
menopause management
,
patient questionnaire
,
period
,
personalized medicine
,
predictive analytics
,
specialist referral
,
women’s health
Category(s):
Software & Algorithms
,
Software & Algorithms > Programs
,
Software & Algorithms > Digital Health
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Medical Devices
,
Medical Devices > FemTech
MEDREX (Case No. 2024-244)
Summary: UCLA researchers have developed a new software package to reconcile medication lists between different electronic health records. Background: Reconciliation is a crucial process that ensures patients’ medication lists are accurate. This process is especially important for patients with memory impairments, who may be more vulnerable...
Published: 10/18/2024
|
Inventor(s):
Li Zhou
,
Richard Korf
,
Cindy Liu
,
Edmond Wen
,
Advaith Gowrishetty
,
Jonathan Xu
,
Nicole Ju
Keywords(s):
Software
,
Software & Algorithms
,
Software Development Tools
,
Software-enabled learning
Category(s):
Software & Algorithms
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Software & Algorithms > Digital Health
,
Software & Algorithms > Programs
,
Software & Algorithms > Data Analytics
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
A Method and System for Pre-processing Medical Images (Case No. 2024-177)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel pre-processing computer algorithm for automated medical imaging. Background: The integration of machine learning and artificial intelligence into medical imaging applications offers significant potential to automate the diagnosis of various...
Published: 10/11/2024
|
Inventor(s):
Bahram Jalali
,
Callen MacPhee
,
Yiming Zhou
,
Koichiro Kishima
Keywords(s):
3D ultrasound imaging
,
Artificial Intelligence
,
bioimaging
,
Computer Vision
,
histopathology images
,
Machine Learning
,
Medical Imaging
,
MRI
,
X-Ray
Category(s):
Diagnostic Markers > Cancer
,
Diagnostic Markers > Immunology
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Software & Algorithms > Digital Health
,
Software & Algorithms > Image Processing
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
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
Method of Proficient Typing Using a Limited Number of Classes (Case No. 2024-063)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel software algorithm to rapidly predict text using small keyboards for various applications, including mobile computing, gaming, and human-computer interactions. Background: Advancements in mobile computing have drastically changed everyday life...
Published: 11/6/2024
|
Inventor(s):
Jonathan Kao
,
Shreyas Kaasyap
,
John Zhou
,
Johannes Lee
,
Nima Hadidi
Keywords(s):
Advanced Computing / AI
,
advanced computing methods
,
all-optical diffractive computing
,
Artificial Neural Network
,
Artificial Neural Network Artificial Neuron
,
assistive communication
,
background radiation
,
Bandwidth (Computing)
,
Brain computer interface
,
brain machine interface
,
Classroom management software
,
Cloud Computing
,
composite scintillators
,
Database management/data entry
,
deep physical neural network
,
design software
,
edge computing
,
fast scintillators
,
gamma spectroscopy
,
graph neural network
,
HCI (Human Computer Interaction)
,
high-Z organometallics
,
Human/Brain computer interfaces (BCI/HCI)
,
human-centered computing
,
material characterization
,
Medical science computing
,
mobile computing
,
modular robotic system
,
nanocomposite scintillators
,
neural network
,
neural networks
,
neutrino detection
,
Optical computing
,
positron emission tomography (PET)
,
predictive text
,
primary school software
,
radiation detection
,
recurrent neural networks
,
Robotics
,
robotics control
,
scintillators
,
second harmonic generation
,
secondary school software
,
self-sustaining computing
,
soft robotics
,
Software
,
Software & Algorithms
,
Software Development Tools
,
Software-enabled learning
,
Spatial computing
,
Stochastic Computing (SC)
,
T6 keyboard
,
T9 keyboard
,
visual computing
,
wafer-scale computing
Category(s):
Software & Algorithms
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Software & Algorithms > Communication & Networking
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