Showing 21,401 - 21,420 results of 26,849 for search 'evaluation computing', query time: 0.20s Refine Results
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    Dental magnetic resonance imaging for bone loss assessment and disease activity classification in severe periodontitis by Arne Lauer, Luisa Schulte, Artid Skenderi, Nouha Tekiki, Alexander Juerchott, Meysam Sohani, Maurice Ruetters, Franz Sebastian Schwindling, Peter Rammelsberg, Mathias Nittka, Sabine Heiland, Martin Bendszus, Tim Hilgenfeld

    Published 2025-06-01
    “…Abstract Objectives To evaluate the reliability and accuracy of dental MRI (dMRI) for volumetric infrabony and furcation bone loss compared to cone-beam computed tomography (CBCT) and to correlate to clinical signs of inflammation in patients with severe periodontitis. …”
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  7. 21407

    Quantification of Estrogen Receptor-Alpha Expression in Human Breast Carcinomas With a Miniaturized, Low-Cost Digital Microscope: A Comparison with a High-End Whole Slide-Scanner. by Oscar Holmström, Nina Linder, Mikael Lundin, Hannu Moilanen, Antti Suutala, Riku Turkki, Heikki Joensuu, Jorma Isola, Vinod Diwan, Johan Lundin

    Published 2015-01-01
    “…Here we present a low-cost, cloud-connected digital microscope for applications at the point-of-care. We evaluate the performance of the device in the digital assessment of estrogen receptor-alpha (ER) expression in breast cancer samples. …”
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    A pilot study of cognitive training with and without transcranial direct current stimulation to improve cognition in older persons with HIV-related cognitive impairment by Ownby RL, Acevedo A

    Published 2016-10-01
    “…Pre- and post-training changes were evaluated via analysis of covariance yielding estimates of effect size. …”
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    Enhancing microgrid forecasting accuracy with SAQ-MTCLSTM: A self-adjusting quantized multi-task ConvLSTM for optimized solar power and load demand predictions by Ehtisham Lodhi, Nadia Dahmani, Syed Muhammad Salman Bukhari, Sujan Gyawali, Sanjog Thapa, Lin Qiu, Muhammad Hamza Zafar, Naureen Akhtar

    Published 2024-10-01
    “…The SAQ-MTCLSTM incorporates a sophisticated architecture that combines convolutional and LSTM layers with self-aware quantization to enhance computational efficiency and model adaptability. This allows for effective knowledge transfer, improved data utilization, and the capture of intricate temporal patterns. …”
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