Clinical characteristics of COVID-19 in children and adolescents: insights from an Italian paediatric cohort using a machine-learning approach by Carlo Giaquinto, Daniela Paolotti, Daniele Donà, Stefania Fiandrino, Piero Poletti, Michael Davis Tira, Costanza Di Chiara

“…First, we apply an unsupervised machine-learning algorithm to cluster individuals into groups. Second, we classify new patient risk groups using a random forest classifier model based on sociodemographic information, pre-existing medical conditions, vaccination status and the VOC as predictive variables. …”
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Development of policy research-evidence organizer and public health-policy evaluation tool (prophet): a computing paradigm for promoting evidence-informed policymaking in Nigeria by Kingsley Otubo Igboji, Chigozie Jesse Uneke, Fergus U. Onu, Onyedikachi Chukwu

“…It strategically evaluates and assess level of evidence content, and predict implementation prospects of health policy documents.…”
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Loneliness, insomnia symptoms, social jetlag, and vitamin D deficiency in relation to mental health problems in Japanese female university students: a cross-sectional study by Nodoka Yamashita, Shioka Ishii, Yoriko Kotoku, Takuya Shuo, Hiromi Eto, Hideaki Kondo

“…Loneliness was assessed using the Three-Item Loneliness Scale. Factors predicting mental health problems with a K6 score ≥ 5 were explored using the Mann–Whitney U test, Fisher’s exact probability test, and classification and regression tree (CART) analysis. …”
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Identification and Validation of Key Genes Related to Lipophagy in Osteoporosis by Hu YX, Zuo ML, Wu Y, Yang Y, Shi XB, Zhang Q, Wu J, Xie RQ, Bi Y, Lin B, Mo C

“…In addition, we constructed a nomogram to predict the incidence of OP patients. Subsequently, multiple bioinformatics tools were used to reveal the associations between key genes and OP. …”
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Comparative estimation of the effectiveness of the Khorana, Vienna CATS, and TiC-Onco scores and the vWF/ADAMTS13 ratio in identifying a high risk of thrombotic complications in pa... by A. V. Vorobеv, A. G. Solopova, V. O. Bitsadze, M. M. Baeva, M. E. Sosnyagova, V. N. Galkin, D. O. Utkin, A. D. Makatsariya

“…The Khorana, Vienna CATS, and TiC-Onco scores demonstrate moderate accuracy in predicting thrombosis in cancer patients, partly due to their inability to consider the individual characteristics of endothelial dysfunction and/or overestimation of the impact of “silent” genetic mutations. …”
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Post-hoc Evaluation of Sample Size in a Regional Digital Soil Mapping Project by Daniel D. Saurette, Richard J. Heck, Adam W. Gillespie, Aaron A. Berg, Asim Biswas

“…Furthermore, the comparison of the optimal maps to the reference maps showed little difference in the global statistics (concordance correlation coefficient and root mean square error) and spatial trends of the data, confirming that the optimal sample size was sufficient for creating predictions of similar accuracy to the full calibration dataset. …”
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Epidemiological surveillance of HIV-1 transmitted drug resistance among newly diagnosed individuals in Shijiazhuang, northern China, 2014-2015. by Xianfeng Wang, Xiaosong Liu, Feng Li, Hong Zhou, Jiefang Li, Yingying Wang, Lihua Liu, Shujun Liu, Yi Feng, Ning Wang

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Development of ultra-short PCR assay to reveal BRAF V600 mutation status in Thai colorectal cancer tissues. by Nunthawut Chat-Uthai, Pichpisith Vejvisithsakul, Sutthirat Udommethaporn, Puttarakun Meesiri, Chetiya Danthanawanit, Yannawan Wongchai, Chinachote Teerapakpinyo, Shanop Shuangshoti, Naravat Poungvarin

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Effects of trap confinement on personality measurements in two terrestrial rodents. by Allison M Brehm, Sara Tironi, Alessio Mortelliti

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Research on the Movement Patterns of Bed-load Streaky Structure Transport and the Mechanism of Fluid-solid Coupling by YAO Jiateng, XIE Xiaoxi, WANG Hao, ZHAO Lin, XIE Haonan, ZHEN Rongtian

“…Based on the located centroids and vector velocities of bedload particles, the Kalman filter algorithm was employed to calculate both measured and predicted values under the given conditions. …”
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Dedicated homeless clinics reduce inappropriate emergency department utilization by Chad T. Holmes, Katherine A. Holmes, Andrew MacDonald, Frank R. Lonergan, Joel J. Hunt, Sajid Shaikh, Radhika Cheeti, James P. D'Etienne, Nestor R. Zenarosa, Hao Wang

“…The New York University algorithm was used to determine appropriate ED utilization. …”
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Development and validation of a prognostic staging system for primary plasma cell leukemia by Mengru Tian, Gang An, Weijun Fu, Wenqiang Yan, Lu Li, Chunyan Sun, Zhenyu Li, Lijuan Chen, Aijun Liao, Guangxun Gao, Xiaoqi Qin, Mengyao Li, Chunrui Li, Hua Xue, Li Gao, Yi Wang, Aili He, Fan Zhou, Dongmei Guo, Yujun Dong, Zhihong Fang, Xiaoxia Chu, Jianqing Mi, Chengcheng Fu, Hui Zeng, Shuling Hou, Xiaotao Wang, Hua Wang, Yongqiang Wei, Xinyue Liang, Xingcheng Yi, Yue Sun, Lugui Qiu, Yun Dai, Fengyan Jin

“…Univariate and multivariate analyses were conducted to identify variables predicting overall survival (OS) to develop a staging system. …”
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An Upscaling-Based Strategy to Improve the Ephemeral Gully Mapping Accuracy by Solmaz Fathololoumi, Daniel D. Saurette, Harnoordeep Singh Mann, Naoya Kadota, Hiteshkumar B. Vasava, Mojtaba Naeimi, Prasad Daggupati, Asim Biswas

“…Employing the Random Forest (RF) algorithm, this study executed three distinct strategies for EGs identification. …”
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Formation of Whipped Yeast-Free Bread Crumb with Intensive Microwave Convective Baking by Gazibeg O. Magomedov, Anatoly А. Khvostov, Aleksey А. Zhuravlev, Magomed G. Magomedov, Aleksei S. Taratukhin, Inessa V. Plotnikova

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Factores clave en la práctica de la Ciencia Abierta. Un análisis multivariado en el contexto universitario = Key Factors in Open Science Practice: A Multivariate Analysis within th... by Sebastián Araya-Pizarro, Héctor García-Leal

“…Data were analyzed using descriptive statistical techniques, association tests, and multivariate analysis (binary logistic regression and K-means algorithm). Results revealed that the willingness to engage in open science is strongly influenced by knowledge, interest, and educational level, and moderately by the participant’s role. …”
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Development and validation of a nomogram for differentiating immune checkpoint inhibitor-related pneumonitis from pneumonia in patients undergoing immunochemotherapy: a multicenter... by Linli Duan, Guanglu Liu, Zijie Huang, Rong Chen, Di Mo, Yuxiao Xia, Jiazhu Hu, Mengzhang He

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Bundled assessment to replace on-road test on driving function in stroke patients: a binary classification model via random forest by Lu Huang, Lu Huang, Xin Liu, Jiang Yi, Yu-Wei Jiao, Tian-Qi Zhang, Guang-Yao Zhu, Shu-Yue Yu, Zhong-Liang Liu, Min Gao, Xiao-Qin Duan

“…Furthermore, the established random forest classification model has demonstrated efficacy in predicting on-road test outcomes, which is worthy of further clinical application.…”
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Mapping recent timber harvest activity in a temperate forest using single date airborne LiDAR surveys and machine learning: lessons for conservation planning by G. Burch Fisher, Andrew J. Elmore, Matthew C. Fitzpatrick, Darin J. McNeil, Jeff W. Atkins, Jeffery L. Larkin

“…In this paper, we develop a timber harvest mapping workflow using machine learning (XGBoost algorithm) and single campaign airborne light detection and ranging (LiDAR) surveys for the state of Pennsylvania, USA. …”
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Integrative genomic analysis and diagnostic modeling of osteoporosis: unraveling the interplay of autophagy, osteogenesis, adipogenesis, and immune infiltration by Lin-Jing Han, Jian-Zong Zhu, Jian-Zong Zhu, Hong-Cai Liu, Xiao-Sheng Lin, Xiao-Sheng Lin, Shu-Zhong Yang

“…Our study formulates a predictive diagnostic model for OP by analyzing differential gene expression, thereby improving early diagnosis and therapeutic approaches.MethodsUsing GSE62402, GSE56815, and GSE35958 datasets from the Gene Expression Omnibus (GEO) database, we identified differentially expressed genes (DEGs) via R packages, and evaluated the underlying molecular mechanisms by network analysis. …”
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Permeability evolution of the thick Cretaceous aquifer and the high-level bed separation water accumulation model during coal mining by Wei QIAO, Xiangsheng MENG, Juan YANG, Liangang LI, Qijing LIANG, Mengnan LIU, Zhihe TAO, Changmin HAN, Weiteng KONG

“…Hydraulic tomography inversion technology, based on the Simultaneous Sequential Linear Estimation (SimSLE) algorithm, was used to analyze the permeability evolution of the aquifer during mining. …”
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