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  1. 28301

    Development of a hip osteoarthritis index for gait quality assessment: a data-driven comparative study by Kamyar Rahmani, Mansour Davoudi, Mohammad Sajjad Alamdar, Rezvan Nasiri

    Published 2025-08-01
    “…For healthy-patient, affected-unaffected leg, and severity grades classifications the accuracy of all models ranged around $$86.5\pm 2.5\%$$ , $$89.5\pm 1.5\%$$ , and $$40.5\pm 1.5\%$$ , respectively, with no significant differences ( $$p>0.16$$ ). …”
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    Establishment of a Novel Risk Stratification System Integrating Clinical and Pathological Parameters for Prognostication and Clinical Decision‐Making in Early‐Stage Cervical Cancer... by Haiying Wu, Lin Huang, Xiangtong Chen, Yi OuYang, JunYun Li, Kai Chen, Xiaodan Huang, Foping Chen, XinPing Cao

    Published 2024-11-01
    “…The performances of the model were compared with the conventional FIGO 2018 and 9th edition T or N stage classifications. Results RPA divided patients into four risk groups with distinct survival: 5‐year OS for RPA I to IV were 98%, 95%, 85.5%, and 64.2%, respectively, in training cohort; and 99.5%, 93.2%, 85%, and 68.3% in internal validation cohort (log‐rank p < 0.001). …”
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  7. 28307

    Neurophysiological findings in Attention Deficit Hyperactivity Disorder, a Pandora’s box with therapeutic implications by Montserrat Gerez-Malo, Armando Tello, Maria Jimena Martin-Salas, Lauro Castanedo, Arturo Mendizábal, Oscar Meneses Luna, Leslie Quintanar, Carlos Acosta

    Published 2025-03-01
    “…C2: Centrotemporal spiles, hyperexcitable network: carbamazepine. C3: Bisynchronous spike-waves complexes, thalamocortical involvement: valproic. …”
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    Structure of acute intestinal infections in the Arkhangelsk region from 2020 to 2022. A clinical case of a mixed form of acute intestinal infection by М. A. Pozdeeva, Yu. S. Tsvetkova, M. A. Kashunina

    Published 2024-11-01
    “…Acute intestinal infections are a broad group of diseases, polyetilogical and extremely diverse in their composition, epidemiology and clinical manifestations. One of the key classifications is the division of pathogens into bacterial and viral. …”
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  13. 28313

    Study on landslide hazard risk in Wenzhou based on slope units and machine learning approaches by Dengjie Kang, Sheng Dan, Zhang Hua, Lu Jingyi, Wang Chenlu, Wang Zhenguo, Wang Shaohua

    Published 2025-03-01
    “…This results in uniformly high-risk classifications for hilly areas, complicating practical engagement and increasing management costs. …”
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