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Search Results - jeffrey+chiang
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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
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
Automated Biomarker Prediction Using Optical Coherence Tomography (Case No. 2020-467)
Summary: UCLA researchers in the Department of Computational Medicine have developed a computer program capable of automatically and accurately diagnosing optical diseases using OCT. Background: Optical diseases, such as age-related macular degeneration (AMD), are serious issues that, if left untreated, can result in partial and even complete blindness....
Published: 7/22/2024
|
Inventor(s):
Eran Halperin
,
Nadav Rakocz
,
Jeffrey Chiang
,
Muneeswar Gupta
,
Srinivas Sadda
Keywords(s):
Image Processing
,
Medical Imaging
,
Software & Algorithms
Category(s):
Medical Devices > Medical Imaging
,
Software & Algorithms > Image Processing
Detection of Dicrotic Notch in Arterial Pressure and Photoplethysmography Signals Using Iterative Envelope Mean Filter (Case No. 2024-034)
Summary: UCLA Researchers in the Department of Anesthesiology have developed an iterative envelope mean (IEM) method for the detection of specific features in arterial pressure monitoring applications. Background: The cardiac cycle consists of the distinct systolic and diastolic phases. The transition from the contracted, systolic phase to the...
Published: 10/24/2024
|
Inventor(s):
Maxime Cannesson
,
Ravi Pal
,
Akos Rudas
,
Jeffrey Chiang
,
Sungsoo (Danny) Kim
Keywords(s):
arrhythmia
,
arterial blood pressure (ABP)
,
cardiac cycle
,
Cardiac Electrophysiology
,
Cardiac failure
,
Cardiac Magnetic Resonance Imaging
,
cardiometabolic disease
,
cardiopulmonary illness
,
Cardiovascular
,
Cardiovascular Disease
,
Cardiovascular Disease Nephropathy
,
cardiovascular modeling
,
cardiovascular prediction
,
cardiovascular therapeutic solution
,
diastolic
,
diastolic phase peak
,
dicrotic notch
,
feature extraction tool
,
iterative envelope method (IEM)
,
Medical Device
,
medical device cardiac monitoring
,
Medical Device Poly(Methyl Methacrylate)
,
Medical Devices and Materials
,
non-invasive cardiac monitoring
,
photoplethysmography (PPG)
,
Smart medical device
,
systolic
,
tachycardia
,
wearable medical device
,
wearable medical devices
Category(s):
Medical Devices
,
Medical Devices > Monitoring And Recording Systems
,
Platforms
,
Platforms > Diagnostic Platform Technologies
,
Software & Algorithms
,
Diagnostic Markers > Targets And Assays
,
Diagnostic Markers
A Uniform AI Framework for Automated Detection of Disease-Related Risk Factors in 3D Medical Imaging Data
Summary: UCLA researchers from the Departments of Anesthesiology & Perioperative Medicine, Ophthalmology, Computational Medicine, and Computer Science have developed a novel uniform framework to diagnose disease-related risk factors in any volumetric medical imaging data. Background: Automated diagnosis of medical imaging is undoubtedly important...
Published: 10/4/2024
|
Inventor(s):
Oren Avram
,
Eran Halperin
,
Berkin Durmus
,
Nadav Rakocz
,
Jeffrey Chiang
,
Srinivas Sadda
Keywords(s):
Advanced Computing / AI
,
AI algorithms
,
Artifical Intelligence (Machine Learning, Data Mining)
,
Artificial Intelligence
,
Biomarker
,
Biomedical Engineering
,
Computer-Aided Design
,
Deep Learning
,
Imaging
,
Magnetic Resonance Imaging
,
Medical Imaging
Category(s):
Software & Algorithms
,
Software & Algorithms > Digital Health
,
Software & Algorithms > Image Processing
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Medical Devices > Medical Imaging
AI Models for Ocular Diseases Using Optical Coherence Tomography (Case No. 2022-113)
Summary: UCLA researchers in the Department of Computational Medicine have developed a computer program capable of automatically and accurately diagnosing optical diseases using OCT. Background: Optical diseases, such as age-related macular degeneration, are serious issues that, if left untreated, can result in partial and even complete blindness....
Published: 10/31/2024
|
Inventor(s):
Jeffrey Chiang
,
Srinivas Sadda
,
Eran Halperin
Keywords(s):
Algorithm Optical Coherence Tomography
,
Artificial Intelligence
,
Eye Surgery
,
Intraocular Lens
,
Lens (Optics)
,
Macular Degeneration
,
Optical Coherence
,
Optical Microscope
,
Optical Tomography
Category(s):
Software & Algorithms
,
Software & Algorithms > Image Processing
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Medical Devices > Medical Imaging