Showing 841 - 860 results of 919 for search '"Fujian"', query time: 0.05s Refine Results
  1. 841

    A nomogram for predicting prognosis for young cervical neuroendocrine carcinoma: A SEER-based study and external validation by Ning Xie, Haijuan Yu, Jie Lin, Sufang Deng, Linying Liu, Yang Sun

    Published 2025-01-01
    “…Therefore, this study aims to develop an individualized prognostic nomogram for young NECC patients.Methods360 young (≤45 years old) NECC patients were retrospectively selected from the Surveillance, Epidemiology and End Results (SEER) database and were randomly located to a training cohort and an internal validation cohort in a ratio of 7:3. Data from Fujian Cancer Hospital was used as an external validation cohort. …”
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    Effects of Soil Properties on Pb, Cd, and Cu Contents in Tobacco Leaves of Longyan, China, and Their Prediction Models by Wei Xi, YuanYe Ping, HaiYang Cai, Qian Tan, Chaoyang Liu, Junru Shen, YaWen Zhang

    Published 2023-01-01
    “…Longyan City in Fujian Province is one of China’s top-quality tobacco-producing areas and plays an essential role in local economic development. …”
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    Genetic Diversity of <i>Diaphorina citri</i> and Its Endosymbiont Across Diffusion Frontier and Epidemic Areas of Citrus Huanglongbing in China by Jin Yang, Ai-Jun Huang, Jun Zhou, Ping You, Xiang Li, Han Luo, Long Yi

    Published 2025-01-01
    “…We identified three dispersal paths: (1) migration of the Yunnan population to Sichuan, Guizhou, and Guangxi; (2) movement of the Guangdong population to Fujian, Jiangxi, and Zhejiang; and (3) dispersal of the Guangdong population to Hunan and Guangxi. …”
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    Advancing Horticultural Crop Loss Reduction Through Robotic and AI Technologies: Innovations, Applications, and Practical Implications by H. W. Gammanpila, M. A. Nethmini Sashika, S. V. G. N. Priyadarshani

    Published 2024-01-01
    “…For instance, Ji et al. in 2007 developed an artificial neural network (ANN)-based system for rice yield prediction in Fujian, China, improving accuracy over traditional models. …”
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