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    Identification of gene signatures and potential pharmaceutical candidates linked to COVID-19-related depression based on gene expression profiles by Shaojun Chen, Yiyuan Luo, Lihua Zhang

    Published 2025-08-01
    “…Subsequently, we employed two machine learning analyses—least absolute shrinkage and selection operator (LASSO) and random forest algorithms– to pinpoint shared hub gene between the two diseases. …”
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  3. 243

    Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment by Chuanyu Ma, Chuanyu Ma, Guandu Li, Xiaohan Song, Xiaochen Qi, Tao Jiang

    Published 2025-05-01
    “…IntroductionProstate adenocarcinoma (PRAD) is an extremely widespread site of urological malignancy and is the second most common male cancer in the world. Currently, research progress in immunotherapy for prostate treatment is slower compared to other tumours, which is mainly considered to be caused by the low rate of immune response in prostate cancer as a cold tumour. …”
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    Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

    Published 2025-02-01
    “…The texts of these 290 articles were studied, and finally 149 articles related to the selected topic and the literature and background of this research were used. In fact, the general goal and main question of this research was to model the innovation process centered on artificial intelligence, was carried out successfully with a very low model error during the test. …”
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    Predicting Resistance and Survival of HCC Patients Post-HAIC: Based on Shapley Additive exPlanations and Machine Learning by Yao F, Miao J, Quan B, Li J, Tang B, Lu S, Yin X

    Published 2025-05-01
    “…Fan Yao,1,2,* Jianliang Miao,3,* Bing Quan,1,2 Jinghuan Li,1,2 Bei Tang,1,2 Shenxin Lu,1,2 Xin Yin1,2 1Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China; 2National Clinical Research Center for Interventional Medicine, Shanghai, People’s Republic of China; 3First Affiliated Hospital of Dalian Medical University, Dalian Medical University, Dalian, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xin Yin, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 136 Yi Xue Yuan Road, Shanghai, People’s Republic of China, Email yin.xin@zs-hospital.sh.cnPurpose: To establish prediction models using Shapley Additive exPlanations (SHAP) and multiple machine learning (ML) algorithms to identify clinical features influencing hepatic arterial infusion chemotherapy (HAIC) resistance and survival in patients with hepatocellular carcinoma (HCC).Patients and Methods: We recruited 286 patients with unresectable HCC who underwent HAIC. …”
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  14. 254

    Supporting self-management with an internet intervention for low back pain in primary care: a RCT (SupportBack 2) by Adam W A Geraghty, Taeko Becque, Lisa C Roberts, Jonathan Hill, Nadine E Foster, Lucy Yardley, Beth Stuart, David A Turner, Gareth Griffiths, Frances Webley, Lorraine Durcan, Alannah Morgan, Stephanie Hughes, Sarah Bathers, Stephanie Butler-Walley, Simon Wathall, Gemma Mansell, Malcolm White, Firoza Davies, Paul Little

    Published 2025-04-01
    “…Interventions Participants were block randomised by a computer algorithm (stratified by severity and centre) to one of three trial arms: (1) usual care, (2) usual care + internet intervention and (3) usual care + internet intervention + telephone support. …”
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    Hyperspectral estimation of chlorophyll density in winter wheat using fractional-order derivative combined with machine learning by Chenbo Yang, Chenbo Yang, Meichen Feng, Juan Bai, Hui Sun, Rutian Bi, Lifang Song, Chao Wang, Yu Zhao, Wude Yang, Lujie Xiao, Meijun Zhang, Xiaoyan Song

    Published 2025-01-01
    “…The main results were as follows: For the 3 types of FOD, GL-FOD was suitable for analyzing the change process of the original spectral curve towards the integer-order derivative spectral curve. …”
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    Influence of micro-topography on the spatial heterogeneity of above-ground biomass: Lessons from the Qinglan Port Mangrove Nature Reserve, China by Meihuijuan Jiang, Penghua Qiu, Dezhi Wang, Minghui Wu, Ruiquan Lai, Xinqing Zou, Tingting Si, Hui Li, Qidong Shi, Yi Lin, Genzong Xie, Yanli Yang, Siang Wan

    Published 2025-07-01
    “…Using UAV LiDAR point cloud and high-resolution orthophotos, we identified the study area’s micro-topography types and divided it into five tidal zones. We employed the random forest algorithm to map the spatial distribution of mangrove above-ground biomass (AGB), and used geographic detectors and structural equation model (SEM) to study micro-topography’s impact on AGB spatial differentiation. …”
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