Search Results - artificial+intelligence%2fmachine+learning+models

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Methods and Systems for Low-Cost Medical Image Annotation Using Non-experts (Case No. 2025-108)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed an AI-based interface designed to enable individuals without specialized training to identify arthritis in medical imaging. Background: The use of artificial intelligence (AI) for medical imaging analysis holds great promise for the future of healthcare....
Published: 7/23/2025   |   Inventor(s): Xiang Chen, Youngseung Jeon, Christopher Hwang
Keywords(s): 3D tissue imaging, AI-guided diagnostics, AI-guided medical imaging, AI-guided medical intervention, arthritis, Artifical Intelligence (Machine Learning, Data Mining), Artificial Intelligence, artificial intelligence algorithms, artificial intelligence augmentation, artificial intelligence/machine learning models, Artificial Neural Network, bioimaging, Computer-Aided Diagnosis, computer-aided radiology, Diagnostic Markers & Platforms, Diagnostic Test, diagnostics, generative artificial intelligence, Image Analysis, Image Resolution, Imaging, infrared thermal imaging, Machine Learning, machine learning modeling, machine perception, Magnetic Resonance Imaging Medical Physics, Magnetic Resonance Imaging Pathology, Medical artificial intelligence (AI), Medical diagnostics, Medical Imaging, Microscopy And Imaging, non-invasive imaging, osteoarthritis, radial MRI, radiologic imaging, Radiology, Radiology / Radiomitigation, radiosurgery
Category(s): Software & Algorithms, Software & Algorithms > AI Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Digital Health, Software & Algorithms > Image Processing, Life Science Research Tools, Life Science Research Tools > Lab Equipment, Life Science Research Tools > Microscopy And Imaging, Medical Devices, Medical Devices > Medical Imaging, Medical Devices > Monitoring And Recording Systems, Therapeutics, Therapeutics > Musculoskeletal Disease, Therapeutics > Radiology
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: 7/22/2025   |   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
Monitoring Structural Health Using Diffractive Optical Processors (Case No. 2025-201)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel structural health monitoring system that is highly accurate and cost effective, addressing limitations in current infrastructure and civil health monitoring and a rise in public safety concerns. Background: The need for structural health monitoring...
Published: 7/25/2025   |   Inventor(s): Aydogan Ozcan, Ertugrul Taciroglu, Yuntian Wang, Yuhang Li
Keywords(s): 3D structures, Adaptive Optics, AI-generated images and content, all-optical diffractive computing, all-optical transformation, analog computing, analog optical computing, Analogue Electronics, Artifical Intelligence (Machine Learning, Data Mining), Artificial Intelligence, artificial intelligence algorithms, artificial intelligence augmentation, artificial intelligence/machine learning models, artificial-intelligent materials, civil engineering, civil infrastructure, civil monitoring, computational imaging, computational imaging task, Construction, deep diffractive network, Diffraction, diffractive design, diffractive image reconstruction, diffractive network, diffractive processor, diffractive surface, digital image reconstruction, electromagnetic spectrum, Electro-Optics, Image Analysis, Image Processing, Image Resolution, image restoration, image signal processing, Imaging, Infrastructure, Lens (Optics), linear optics, Nanostructure, optical processor, optically-guided structural monitoring, Optics, passive light-matter interactions, security imaging, Signal Reconstruction, Structural health monitoring, structural health monitoring (SHM), structure monitoring, Structures
Category(s): Electrical, Electrical > Signal Processing, Electrical > Imaging, Materials, Materials > Construction Materials, Electrical > Visual Computing, Electrical > Computing Hardware, Electrical > Instrumentation, Energy & Environment, Energy & Environment > Energy Efficiency, Software & Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Image Processing, Software & Algorithms > Programs
Batch Processing Automation for Imaris Stitcher (Case No. 2025-089)
Summary: Researchers in UCLA’s Department of Neurobiology have developed a novel software tool that enhances the capabilities of Imaris Stitcher. The tool enables batch processing and automated execution of multiple image stitching jobs, significantly improving workflow efficiency and reducing hands-on time. This results in readily available,...
Published: 7/14/2025   |   Inventor(s): Ian Bowman, Mitchell Rudd, Hong Wei Dong
Keywords(s): 3D tissue imaging, 3D ultrasound imaging, Artifical Intelligence (Machine Learning, Data Mining), Artificial Intelligence, artificial intelligence algorithms, artificial intelligence augmentation, artificial intelligence/machine learning models, artificial-intelligent materials, bioimaging, Cell Counting/Imaging, cell imaging, cell mapping, computational imaging, Data Acquisition, Data Aggregator, Data Analytics, Data Recovery, Data Structure, Fluorescence Microscope, histopathology images, Image Analysis, image restoration, image signal processing, Imaging, Magnetic Resonance Imaging, Medical artificial intelligence (AI), Medical Imaging, Microscope, Microscopy, Microscopy And Imaging, Molecular Imaging, multi-contrast imaging, Neuroimaging, non-invasive imaging, pathology image analysis, Phase-Contrast Imaging, three dimensional imaging, volumetric image
Category(s): Software & Algorithms, Software & Algorithms > AI Algorithms, Software & Algorithms > Digital Health, Software & Algorithms > Image Processing
Non-invasive Pain Measurement of Infants and Toddlers Using Acoustic Features of Cries (Copyright; Case No. 2018-327)
Summary: Researchers in the UCLA Semel Institute for Neuroscience and Human Behavior have developed a novel, non-invasive pain measurement tool for neonates. Background: Pain management in neonatal care remains a critical unmet need. Approximately 90% of premature infants undergo painful procedures, yet pain is only reported in 45% of cases. Current...
Published: 4/21/2025   |   Inventor(s): Ariana Anderson
Keywords(s): acoustics, artificial intelligence/machine learning models, Digital Signal Processing, Machine Learning Pain Management, Monitoring (Medicine), non-invasive monitoring, Pain Treatment, pediatrics
Category(s): Diagnostic Markers > Pediatrics, Medical Devices > Monitoring And Recording Systems, Platforms > Diagnostic Platform Technologies, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > AI Algorithms, Software & Algorithms > Data Analytics, Software & Algorithms > Digital Health, Therapeutics > Critical Care, Therapeutics > Psychiatry And Mental Health
Event-Driven Integrate and Fire (EIF) Neuron Circuit for Neuromorphic Computing System (Case No. 2024-275)
Summary: Researchers in the UCLA Department of Electrical and Computer Engineering have developed an energy efficient neuromorphic computing architecture. Background: Widespread growth in demand for artificial intelligence systems has highlighted limitations in current central processing unit (CPU) designs, particularly in terms of energy efficiency...
Published: 3/4/2025   |   Inventor(s): Mau-Chung Chang, Chao Jen Tien, Yong Hei
Keywords(s): Advanced Computing / AI, advanced computing methods, AI hardware, analog computing, Artifical Intelligence (Machine Learning, Data Mining), artificial electromagnetic materials, Artificial Intelligence, artificial intelligence algorithms, artificial intelligence augmentation, artificial intelligence/machine learning models, artificial intelligence-generated content, Artificial Neural Network, Artificial Neural Network Artificial Neuron, artificial presenting cells, artificial-intelligent materials, Cloud Computing, computational efficiency, computational imaging, compute-in-memory, Computer Aided Learning, Computer Architecture, Computer Monitor, Computer Vision, CPU design, deep neural networks (DNN), Energy Density, Energy Efficiency, event-driven processing, generative artificial intelligence, latency encoding, low latency computing, low-power architecture, matrix multiplication, Medical artificial intelligence (AI), Neuromorphic computing, offline learning, online learning, spike neural networks (SNN), Supercomputer
Category(s): Electrical, Electrical > Signal Processing, Electrical > Electronics & Semiconductors, Electrical > Computing Hardware, Software & Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning
Positive Unlabeled Learning With Bias Mitigation for Fair Prediction of Undiagnosed Alzheimer’s Disease (Case No. 2025-113)
Summary: UCLA researchers in the Department of Neurology have developed a software to predict the diagnosis of Alzheimer’s Disease without racial or ethnic biases. Background: Alzheimer’s Disease (AD) represents a major health and economic challenge in the United States. Despite its prevalence, Alzheimer’s remains significantly...
Published: 2/14/2025   |   Inventor(s): Timothy Chang
Keywords(s): Alzheimers disease, artificial intelligence/machine learning models, electronic health records (EHR), medical bias reduction, Neurodegeneration Alzheimer's Disease Predictive Testing, neurological disorders, Neurology, personalized medicine
Category(s): Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Data Analytics, Software & Algorithms > Digital Health, Software & Algorithms > Image Processing, Software & Algorithms > Programs, Diagnostic Markers > Aging, Therapeutics > CNS and Neurology