Search Results - neural+network

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Deep Neural Networks for Real-Time Non-invasive Continuous Peripheral Oxygen Saturation Monitoring (Case No. 2024-227)
Summary: UCLA researchers in the Department of Anesthesiology have developed a novel pulse oximetry methodology utilizing deep neural networks for non-invasive monitoring. Background: In the US alone, over 5 million patients are admitted to the ICU for oxygen saturation monitoring. They, as well as the more than 15 million patients undergoing surgery,...
Published: 7/26/2024   |   Inventor(s): Sungsoo (Danny) Kim, Sohee Kwon, Mia Markey, Alan Bovik, Akos Rudas, Ravi Pal, Maxime Cannesson
Keywords(s): Artifical Intelligence (Machine Learning, Data Mining), Blood Pressure, cardiovascular monitoring, central venous pressure (CVP), Continuous blood pressure monitoring, critical care, Deep learning-based sensing, deep-learning analysis algorithms, heart failure, hemodynamic monitoring, machine learning modeling, Monitoring (Medicine), neural network, non-invasive monitoring, Oxygen, Oxygen Saturation, pulmonary arterial pressure (PAP), Swan-Ganz catheter
Category(s): Medical Devices > Monitoring And Recording Systems, Software & Algorithms > Digital Health
Efficient Stochastic Compute-In-Memory Circuit for Multi-Level or Accumulation (Case No. 2024-122)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel computational hardware that combines stochastic computing with compute-in-memory techniques that improves speed and computational efficiency. Background: In recent years, the need for advanced computational technologies has surged, driven by...
Published: 7/8/2024   |   Inventor(s): Sudhakar Pamarti, Jiyue Yang, Soumitra Pal, Puneet Gupta, Tianmu Li, Wojciech Romaszkan
Keywords(s): computational efficiency, Computer Architecture, Integrated Circuit, Logic Gate, neural network, Stochastic Computing (SC)
Category(s): Electrical > Computing Hardware, Electrical > Electronics & Semiconductors > Circuits
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: 6/10/2024   |   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
DNA Oligo Implementation of Multi-Layer Perception (UCLA Case No. 2021-175)
UCLA researchers in the Department of Chemistry and Biochemistry have developed a novel method for an artificial neural network to solve DNA problems of regression and classification. BACKGROUND: Organisms have diverse cell types that need to be distinguished in a clinical setting. Different cell types are known to express different molecular markers...
Published: 4/8/2024   |   Inventor(s): Roy Wollman
Keywords(s): cell type identification, DNA oligomer, FISH, neural network
Category(s): Life Science Research Tools > Microscopy And Imaging