Search Results - jeffrey+chiang

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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: 4/8/2024 | Inventor(s): Maxime Cannesson, Ravi Pal, Akos Rudas, Jeffrey Chiang, Sungsoo 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: 7/19/2023 | 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

2022-113 AI MODELS FOR OCULAR DISEASES USING OPTICAL COHERENCE TOMOGRAPHY

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: 7/19/2023 | 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

2020-467 Automated Biomarker Prediction Using Optical Coherence Tomography

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: 7/19/2023 | Inventor(s): Eran Halperin, Nadav Rakocz, Jeffrey Chiang, Muneeswar Gupta, Srinivas Sadda

Keywords(s): Image Processing, Medical Imaging, Software & Algorithms

Category(s): Software & Algorithms > Image Processing, Medical Devices > Medical Imaging