Showing 1,101 - 1,120 results of 2,096 for search '"University of California"', query time: 0.07s Refine Results
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    Tolerability and Effectiveness of Regorafenib Treatment in Patients with Unresectable Hepatocellular Carcinoma: Real-World Data from the United States by Finn RS, Iyer R, Kalman RS, Parikh ND, Cabrera R, Babajanyan S, Kaseb AO

    Published 2025-02-01
    “…Richard S Finn,1 Renuka Iyer,2 Richard S Kalman,3 Neehar D Parikh,4 Roniel Cabrera,5 Svetlana Babajanyan,6 Ahmed O Kaseb7 1Department of Medicine, University of California, Los Angeles, CA, USA; 2Department of Medicine, Roswell Park Cancer Institute, Buffalo, NY, USA; 3Department of Medicine, Einstein Medical Center, Philadelphia, PA, USA; 4Division of Gastroenterology and Hepatology, University of Michigan, Ann Arbor, MI, USA; 5Department of Medicine, University of Florida Health, Gainesville, FL, USA; 6US Medical Affairs, Oncology, Bayer Healthcare, Whippany, NJ, USA; 7Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USACorrespondence: Richard S Finn, Department of Medicine, University of California, Los Angeles, CA, USA, Tel +1-310-586-2091, Email rfinn@mednet.ucla.eduIntroduction: While several systemic therapies are available for unresectable hepatocellular carcinoma (uHCC), there is a lack of granular real-world evidence to support the efficacy and safety of these therapies. …”
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    Human activity recognition algorithm based on the spatial feature for WBAN by Chi JIN, Zhijun LI, Dayang SUN, Fengye HU

    Published 2019-09-01
    “…Traditional image-based activity recognition algorithms have some problems,such as high computational cost,numerous blind spots and easy privacy leakage.To solve the problem above,the CCLA (convolution-convolutional long short-term memory-attention) activity recognition algorithm based on the acceleration and gyroscope data was proposed.The convolutional neural network was used to extract spatial features of activity data and got the hidden time series information from the convolutional long short-term memory network.Simulating human brain selecting attention mechanism,attention-encoder was constructed to extract the spatial and temporal features at a higher level.The CCLA algorithm was tested on UCI-HAPT (university of California Irvine-smartphone-based recognition of human activities and postural transitions) public data set,and realized the classification of 12 types of activity with the accuracy of 93.27%.…”
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