Search Results - diagnostic+markers

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AI-Based Wearable Sensor for Dermatology (Case No. 2025-301)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a flexible, cost-effective, AI-enabled wearable sensor that facilitates early, non-invasive diagnosis of allergic contact dermatitis. Background: Allergic contact dermatitis (ACD) is a hypersensitivity reaction of the skin triggered by direct contact...
Published: 8/26/2025   |   Inventor(s): Aydogan Ozcan, Shannon Wongvibulson, Paloma Casteleiro Costa, Gyeo-Re Han, Yuzhu Li
Keywords(s): Artificial Intelligence, artificial intelligence augmentation, artificial intelligence/machine learning models, Artificial Neural Network, artificial-intelligent materials, Computer-Aided Diagnosis, deep neural networks (DNN), Dermatology, electrochemical sensors, Medical artificial intelligence (AI), Signal Processing, Signal-To-Noise Ratio, Skin, skin protection, wearable, wearable electronics, wearable medical device, wearable medical devices, wearable sensors, wearable sensors for health
Category(s): Electrical, Electrical > Flexible Electronics, Electrical > Sensors, Medical Devices > Monitoring And Recording Systems, Therapeutics > Dermatology, Diagnostic Markers
INSPIROMARK (Case No. 2025-293)
Summary: UCLA researchers have developed InspiroMark, a standardized, implantable imaging marker designed to enhance the efficiency, reliability and ease of grafted vessel localization following coronary artery bypass graft (CABG). Background: Coronary Artery Bypass Graft (CABG) surgery is a common procedure used to restore blood flow to the heart....
Published: 8/20/2025   |   Inventor(s): Sneha Shaha, Michael Malig, Sukhneet Dhillon
Keywords(s):  
Category(s): Diagnostic Markers, Medical Devices, Medical Devices > Cardiac, Medical Devices > Medical Imaging > CT, Medical Devices > Medical Imaging > MRI, Medical Devices > Medical Imaging > X-Ray, Medical Devices > Medical Imaging > Fluorescence, Medical Devices > Monitoring And Recording Systems, Medical Devices > Surgical Tools, Therapeutics > Cardiovascular, Therapeutics > Radiology, Therapeutics > Transplant
Subgraph Matching for High-Throughput DNA-Aptamer Secondary Structure Classification and Machine Learning Interpretability (Case No. 2025-104)
Intro Sentence: UCLA researchers in the Department of Mathematics have developed machine learning methods to rapidly identify novel aptamer sequences for target binding to accelerate highly-accurate diagnostic and therapeutic development. Background: Aptamers are single-stranded nucleotide polymers that bind with high affinity to targets such as...
Published: 8/19/2025   |   Inventor(s): Andrea Bertozzi, Anne Andrews, Matthew Tyler, Paolo Climaco, Noelle Mitchell
Keywords(s): Advanced Computing / AI, advanced computing methods, Aptamers, Artifical Intelligence (Machine Learning, Data Mining), artificial intelligence/machine learning models, bioinformatics pipeline, cancer target, clustering, computational efficiency, computational efficiency and analysis, design software, DNA clustering, DNA oligomer, DNA Sequencing, Drug, Drug Delivery, Drug Development, Drug Discovery, drug screening, high throughput, high throughput assays, high throughput testing, high-throughput analysis, High-Throughput Screening, interpretability, pipeline, large-scale parallelization, Machine Learning, machine learning modeling, motif structures, open source, open source code, OpenAI, Pharmaceutical Drug, protein classification, secondary structure, SELEX, sequences of interest, single strand DNA sequences, Software, Software & Algorithms, Software Development Tools, Software-enabled learning, subgraph matching, target binding, target detection, Targeted Therapy, Targets And Assays, tissue targeting accuracy
Category(s): Software & Algorithms, Software & Algorithms > AI Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Data Analytics, Life Science Research Tools, Life Science Research Tools > Research Methods, Life Science Research Tools > Screening Libraries, Platforms, Platforms > Drug Delivery, Diagnostic Markers > Targets And Assays, Diagnostic Markers, Software & Algorithms > Bioinformatics
Lab on a 3D Printer (Case No. 2025-094)
Summary: UCLA researchers in the Department of Bioengineering have developed a novel device capable of performing automated liquid handling to a great degree of precision on a miniaturized scale and with customizable features equipped for any laboratory task. Background: Automated liquid handling is essential in pharmaceutical and biotechnology research...
Published: 8/21/2025   |   Inventor(s): Dino Di Carlo, Shun Ye, Zixin Guan, Artem Goncharov, Vivek Rajasenan, Charlotte Rose McDonough, Tristan Lovely
Keywords(s): 3D biofabrication, 3D Printing, Automation, bioimaging, biomanufacturing, Biomaterial 3D Printing, Biomonitoring, Biosensor, Biotechnology, Drug Discovery, fluid mechanics, graphical user interface, Liquid tracking, mechanical durability, Robotic liquid handling
Category(s): Life Science Research Tools, Medical Devices, Diagnostic Markers, Life Science Research Tools > Lab Equipment, Mechanical
Deep Learning-Enhanced Chemiluminescence Vertical Flow Assay for High-Sensitivity Cardiac Troponin I Testing (Case No. 2025-128)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering & Bioengineering have developed a novel, high-sensitivity chemiluminescence vertical flow assay for rapid cardiac diagnostics, addressing current challenges in both modern and underserved healthcare settings. Background: Point-of-care (POC) testing is performed...
Published: 6/13/2025   |   Inventor(s): Aydogan Ozcan, Gyeo-Re Han, Artem Goncharov, Hyouarm Joung, Dino Di Carlo, Merve Eryilmaz
Keywords(s):  
Category(s): Chemical, Chemical > Instrumentation & Analysis, Diagnostic Markers, Diagnostic Markers > Targets And Assays, Electrical, Electrical > Imaging, Software & Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Therapeutics, Therapeutics > Cardiovascular
Urine-Based Diagnostics for Prostate Cancer (UCLA Case No. 2023-302)
UCLA researchers in the Department of Human Genetics have developed a urine-based method for non-invasive prostate cancer diagnosis. By quantifying secreted and extracellular vesicles proteomes from urine, they identified protein biomarkers that enable accurate diagnosis and risk stratification of prostate cancer, outperforming the current PSA test. BACKGROUND:...
Published: 7/17/2025   |   Inventor(s): Paul Boutros
Keywords(s): biomarkers, Cancer, diagnostics, extracellular vesicle, genitourinary, prostate cancer, prostatic lesion, risk stratification, secreted proteome, urinary proteome, Urine-based
Category(s): Diagnostic Markers
Deep Learning-Enhanced Paper-Based Vertical Flow Assay for High-Sensitivity Troponin Detection Using Nanoparticle Amplification (Case No. 2024-179)
Summary: UCLA researchers from the Departments of Electrical and Computer Engineering and Bioengineering have developed a novel assay for point-of-care testing for acute myocardial infarction. Background: Cardiovascular diseases are responsible for a substantial number of deaths and economic burdens. Acute myocardial infarction (AMI) is an event...
Published: 2/14/2025   |   Inventor(s): Aydogan Ozcan, Gyeo-Re Han, Artem Goncharov, Hyouarm Joung, Dino Di Carlo
Keywords(s): acute myocardial infarction, Assay, Bioassay, biological assays, cardiometabolic disease, cardiopulmonary illness, Cardiovascular, Cardiovascular Disease, Cardiovascular Disease Nephropathy, cardiovascular diseases, cardiovascular modeling, cardiovascular prediction, cardiovascular therapeutic solution, deep-learning analysis algorithms, Flow Device, heart disease mitigation, high-sensitivity cardiac troponin I, Immunoassay, Laminar flow, nanoparticle amplification chemistry, point-of-care testing, Targets And Assays, vertical flow assay
Category(s): Medical Devices, Medical Devices > Monitoring And Recording Systems, Platforms, Platforms > Diagnostic Platform Technologies, Diagnostic Markers, Diagnostic Markers > Targets And Assays
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: 3/26/2025   |   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
Field-Effect Transistor Biosensors Integrated With Porous Media (Case No. 2023-093)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering in collaboration with the University of Chicago have developed a new diagnostic biosensor by combining field-effect transistors with porous media. Background: Point-of-care (POC) and self-testing tools rely on the real-time monitoring of biomarkers in bodily fluids....
Published: 2/14/2025   |   Inventor(s): Aydogan Ozcan, Hyouarm Joung, Hyun-June Jang, Junhong Chen
Keywords(s): Biomarker, biomarkers, Biomaterial, Biosensor, Computer-Aided Diagnosis, Diagnostic Markers & Platforms, Diagnostic Platform Technologies (E.G. Microfluidics), Diagnostic Test, Electrical, Electrical Engineering, electrically-mediated sensing, electrochemical sensors, enzyme functionalization, field-effect transistors (FETs), Medical diagnostics, multiplexed analysis, Point Of Care, point-of-care, porous media, sample matrix effects, transistors
Category(s): Electrical, Electrical > Sensors, Medical Devices, Medical Devices > Monitoring And Recording Systems, Diagnostic Markers, Diagnostic Markers > Targets And Assays, Platforms, Platforms > Diagnostic Platform Technologies
Stain-Free, Rapid, and Quantitative Viral Plaque Assay Using Deep Learning and Holography (Case No. 2022-326)
Intro Sentence: UCLA researchers in the Department of Electrical and Computer Engineering have developed a rapid and stain-free quantitative assay using lens-free holography and deep learning to efficiently and cost-effectively determine the presence of viral plaque-forming units (PFUs) in samples. Background: A broad range of viruses have caused...
Published: 2/14/2025   |   Inventor(s): Aydogan Ozcan, Yuzhu Li, Tairan Liu
Keywords(s): Antiviral Drug, Artifical Intelligence (Machine Learning, Data Mining), Assay, Bioassay, Computer Aided Learning, Diagnostic Markers & Platforms, Diagnostic Platform Technologies (E.G. Microfluidics), Diagnostic Test, Digital Holography, Electrical, Electrical Brain Stimulation, Electrical Breakdown, Electrical Engineering, Electrical Impedance, Electrical Load, Electrical Load Equation Of State, Electrical Resistance And Conductance, Electrical Resistivity And Conductivity, Holography, Immunoassay, Immunoassay Sense (Molecular Biology), Lentivirus Viral Vector, Machine Learning, Machine Learning Autonomous Car Gradient Descent, Machine Learning Pain Management, Machine Learning Particulates Global Climate Model, Network Analysis (Electrical Circuits), Perceptual Learning, Plasmid Trabecular Meshwork Aqueous Humour Viral Vector, Targets And Assays, Transcutaneous Electrical Nerve Stimulation, Transfection Viral Vector, Unsupervised Learning , Viability Assay, Viral Delivery Systems, Viral Envelope, Viral Load
Category(s): Diagnostic Markers, Diagnostic Markers > Targets And Assays, Electrical, Life Science Research Tools, Life Science Research Tools > Research Methods, Life Science Research Tools > Other Reagents, Software & Algorithms > Artificial Intelligence & Machine Learning
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