Mortality and morbidity patterns in Yaoundé, Cameroon: an ICD-11 classification-based analysis by Georges Nguefack-Tsague, Fabrice Zobel Lekeumo Cheuyem, Boris Edmond Noah, Valérie Ndobo-Koe, Adidja Amani, Léa Melataguia Mekontchou, Marie Ntep Gweth, Annick Collins Mfoulou Minso Assala, Marie Nicole Ngoufack, Pierre René Binyom

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基于多轴注意力双通道神经网络模型的食草动物粪便分析方法 by 马光凯, 邓雯心, 杨飞飞, 包衡, 姜广顺

“…本研究构建的网络模型及相关代码已开源，具体内容参见https：//github.com/togo11/classification。…”
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Comparison of conditioning factor classification criteria in large-scale statistically based landslide susceptibility models by M. Sinčić, S. Bernat Gazibara, M. Rossi, S. Mihalić Arbanas

“…Therefore, the paper focuses on the crucial step of classifying continuous landslide conditioning factors for susceptibility modelling by presenting an innovative comprehensive analysis that resulted in 54 landslide susceptibility models to test 11 classification criteria (scenarios which vary from stretched values, partially stretched classes, heuristic approach, classification based on studentized contrast and landslide presence, and commonly used classification criteria, such as natural neighbour, quantiles and geometrical intervals) in combination with 5 statistical methods. …”
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Exploring Chronic Pain in Hemodialysis Patients: An Observational Study Based on the New IASP Classification for ICD-11 by Vittorio Schweiger, Martina Cacciapuoti, Marta Nizzero, Salvatore Simari, Gianmarco Lombardi, Leonardo Gottin, Lisa Stefani, Alvise Martini, Giustino Varrassi, Gabriele Finco, Enrico Polati, Giovanni Gambaro

“…Our study highlights some limitations of the last IASP ICD-11 classification, especially the lack of specific items for some pain features that are very frequent in hemodialysis patients, and not only in that population. …”
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