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    Enhanced enchondroma detection from x-ray images using deep learning: A step towards accurate and cost-effective diagnosis
    (John Wiley and Sons Inc, 2024) Aydin, Simsek, S.; Aydin, A.; Say, F.; Cengiz, T.; Özcan, C.; Öztürk, M.; Okay, E.
    This study investigates the automated detection of enchondromas, benign cartilage tumors, from x-ray images using deep learning techniques. Enchondromas pose diagnostic challenges due to their potential for malignant transformation and overlapping radiographic features with other conditions. Leveraging a data set comprising 1645 x-ray images from 1173 patients, a deep-learning model implemented with Detectron2 achieved an accuracy of 0.9899 in detecting enchondromas. The study employed rigorous validation processes and compared its findings with the existing literature, highlighting the superior performance of the deep learning approach. Results indicate the potential of machine learning in improving diagnostic accuracy and reducing healthcare costs associated with advanced imaging modalities. The study underscores the significance of early and accurate detection of enchondromas for effective patient management and suggests avenues for further research in musculoskeletal tumor detection. © 2024 The Author(s). Journal of Orthopaedic Research® published by Wiley Periodicals LLC on behalf of Orthopaedic Research Society.
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    Escape rate in ac SQUID on Josephson junction based on single- and multi-band superconductors in thermal activation regime
    (B.Verkin Institute for Low Temperature Physics and Engineering of the NAS of Ukraine, 2023) Aydin, A.; Askerzade, I.N.; Askerbeyli, R.
    The escape rate of S?R switching (from superconducting S state to unstable resistive R state) in an ac SQUID with Josephson junction based on single- and multi-band superconductors is investigated by taking the frustration effects in a multi-band superconducting state into account. Using the effective critical current approach, it is shown that the escape rate in thermal activation regime can manifest qualitative features caused by the frustration effects in two- and three-band superconductors. © 2023 Institute for Low Temperature Physics and Engineering. All rights reserved.
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    Escape rate in ac SQUID on josephson junction based on single- and multi-band superconductors in thermal activation regime
    (Aip Publishing, 2023) Aydin, A.; Askerzade, I. N.; Askerbeyli, R.
    The escape rate of S -> R switching (from superconducting S state to unstable resistive R state) in an ac SQUID with Josephson junction based on single- and multi-band superconductors is investigated by taking the frustration effects in a multi-band superconducting state into account. Using the effective critical current approach, it is shown that the escape rate in thermal activation regime can manifest qualitative features caused by the frustration effects in two- and three-band superconductors.