Search Results - siteng+chen

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Deep Learning Algorithm for Detection of Cortical Arousal During Sleep
This invention is an end-to-end deep learning algorithm to detect cortical arousals during sleep using a one-night single lead electrocardiogram (ECG) signal. It is used to accurately detect arousal in home sleep tests, by reducing the false negative rate. The model combines both convolutional neural networks (CNN) and recurrent neural networks (RNN). Background: Sleep...
Published: 3/28/2024   |   Inventor(s): Ao Li, Siteng Chen, Stuart Quan, Linda Powers, Janet Roveda
Keywords(s):  
Category(s): Technology Classifications > Healthcare Portfolios > Sleep Disorders, Technology Classifications > Software & Information Technology > Health IT
Novel Multi-Omics Aging Clock
­A multi-omics clock analyzes multiple layers of omics data with machine learning to predict remaining lifespan of mammals, particularly for animal model studies. Large omics data sets may be used from combinations of genomics, proteomics, lipids, etc. available from blood or other simple sample collection. This tool can robustly capture changes...
Published: 3/12/2024   |   Inventor(s): George Sutphin, Samuel Freitas, Megha Padi, Chen Chen
Keywords(s):  
Category(s): Technology Classifications > Life Sciences > Biomarkers, Technology Classifications > Research Tools > Animal Models, Technology Classifications > Research Tools > Screening assays, Technology Classifications > Research Tools > Simulators and Modeling Tools
Deep Learning Based PV Cell System Design
This technology focuses on enhancement of current photovoltaic (PV) cells to optimize the overall system output of solar electricity. This technology uses a microprocessor based algorithm to monitor PV output in real-time to assist in reconfiguration of PV filters, converters, and inverters parameters for optimal PV cell system performance. Background:...
Published: 4/3/2023   |   Inventor(s): Janet Roveda, Siteng Chen
Keywords(s):  
Category(s): Technology Classifications > Energy, Cleantech & Environmental > Renewable Energy > Solar/Photovoltaic, Technology Classifications > Software & Information Technology > Manufacturing