A Systematic Review and Network Meta-Analysis of Biomedical Mg Alloy and Surface Coatings in Orthopedic Application by XinYue Lu, HongXin Cai, Yu Ru Li, Xinru Zheng, Jiahao Yun, Wenhui Li, XiaoYu Geng, Jae-Sung Kwon, Heng Bo Jiang

“…Network structure and forest plots were created, and ranking probabilities were estimated. …”
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A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols by Nicolas Francos, Daniela Heller-Pearlshtien, José A. M. Demattê, Bas Van Wesemael, Robert Milewski, Sabine Chabrillat, Nikolaos Tziolas, Adrian Sanz Diaz, María Julia Yagüe Ballester, Asa Gholizadeh, Eyal Ben-Dor

“…A machine-learning TF strategy was developed, assembling random forest (RF) spectral-based models to predict the ISS spectral condition using soil samples from two existing SSLs. …”
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Identification of Potential Type II Diabetes in a Large-Scale Chinese Population Using a Systematic Machine Learning Framework by Mingyue Xue, Yinxia Su, Chen Li, Shuxia Wang, Hua Yao

“…Combined with the risk factors selected by LR, we used a decision tree, a random forest, AdaBoost with a decision tree (AdaBoost), and an extreme gradient boosting decision tree (XGBoost) to identify individuals with T2DM, compared the performance of the four machine learning classifiers, and used the best-performing classifier to output the degree of variables’ importance scores of T2DM. …”
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DATA MINING ALGORITHMS FOR PREDICTION OF STUDENT TEACHERS’ PERFORMANCE IN ICT: A SYSTEMATIC LITERATURE REVIEW by Juma Habibu Shindo, Mohamedi Mohamedi Mjahidi, Mohamed Dewa Waziri

“…They are Naive Bayes, K-Nearest Neighbour, Support Vector Machine, Random Forest, and Decision Tree. The findings of this study would assist the government, college tutors, and student teachers in making better decisions to improve ICT performance for pre-service and in-service teachers. …”
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The efficacy of chelated micronutrient fertilisers in tomato cultivation by Volodymyr Sievidov, Oksana Serhienko, Ivan Lebedynskyi, Igor Sievidov

“…The research, conducted during 2018-2021 in film greenhouses at the experimental site of the State Biotechnological University, located in the south eastern part of the Left-Bank Forest-Steppe of Ukraine, examined the F1 indeterminate tomato hybrids Berberana (early maturity) and Bostina (mid-early maturity). …”
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Resistance of old winter bread wheat landraces to tan spot by N. V. Mironenko, N. M. Kovalenko, O. A. Baranova, O. P. Mitrofanova

“…Vavilov: “steppe winter bread wheat (Banatka wheats)”, “North European forest awnless bread wheats (Sandomirka wheats)”, and “Caucasian mountain winter bread wheat”.Conclusion. …”
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Association of Septic Shock with Mortality in Hospitalized COVID-19 Patients in Wuhan, China by Shaoqiu Chen, Zitong Gao, Ling Hu, Yi Zuo, Yuanyuan Fu, Meilin Wei, Emory Zitello, Gang Huang, Youping Deng

“…A prediction model was established using random forest. Results. The mortality of septic shock and nonshock patients with COVID-19 was 96.7% (29/30) and 3.8% (7/182). …”
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Plastome characterization and its phylogenetic implications on Lithocarpus (Fagaceae) by Lifang Yang, Shoujun Zhang, Chunya Wu, Xiaolong Jiang, Min Deng

“…Abstract Background The genus Lithocarpus is a species-rich dominant woody lineage in East Asian evergreen broad-leaved forests. Despite its ecological and economic significance, the plastome structure and evolutionary history of the genus remain poorly understood. …”
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Advanced characterization of deforestation frontiers in Nigeria utilizing deep learning and Bayesian approaches with sentinel-1 SAR imagery by Isiaka Lukman Alage, Yumin Tan, Ahmed Wasiu Akande, Agus Suprijanto

“…Addressing these challenges, we propose an innovative approach that integrates spatial and temporal features for biannual deforestation mapping using synthetic aperture radar data in hotspots, study site 1 (Akure) and study site 2 (Okomu) forest reserve (First and second halves of 2020, 2021, 2022, and 2023). …”
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Spatiotemporal Relationship Between Carbon Metabolism and Ecosystem Service Value in the Rural Production–Living–Ecological Space of Northeast China’s Black Soil Region: A Case Stu... by Yajie Shang, Yuanyuan Chen, Yalin Zhai, Lei Wang

“…The flow of ecological value from forest ecological space to cropland production space represents the main loss pathway. (4) A significant negative correlation exists between carbon metabolism density and ESV, with areas of high correlation predominantly centered around cropland production space. …”
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Reassessing the schedule of the sugar season in maple under climate warming by Gian de Lima Santos, Roberto Silvestro, Sara Yumi Sassamoto Kurokawa, Guillaume de Lafontaine, Sergio Rossi

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Using Deep Learning to Identify High-Risk Patients with Heart Failure with Reduced Ejection Fraction by Zhibo Wang, Xin Chen, Xi Tan, Lingfeng Yang, Kartik Kannapur, Justin L. Vincent, Garin N. Kessler, Boshu Ru, Mei Yang

“…For comparison, we also tested multiple traditional machine learning models including logistic regression, random forest, and eXtreme Gradient Boosting (XGBoost). Model performance was assessed by area under the curve (AUC) values, precision, and recall on an independent testing dataset. …”
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ERBB3-related gene PBX1 is associated with prognosis in patients with HER2-positive breast cancer by Shufen Mo, Haiming Zhong, Weiping Dai, Yuanyuan Li, Bin Qi, Taidong Li, Yongguang Cai

“…Three algorithms, LASSO, RandomForest and XGBoost were combined to identify the signature genes. we construct risk models and generate ROC curves for prediction. …”
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Comparison of the efficacy of seven non-surgical methods combined with mechanical debridement in peri-implantitis and peri-implant mucositis: A network meta-analysis. by Yingjie Bai, Shengao Qin, Bingshuai Lu, Weiyi Wang, Guowu Ma

“…Network meta-analyses include network plots, paired comparison forest plots, league tables, funnel plots, surface under the cumulative ranking area (SUCRA) plots, and sensitivity analysis plots. …”
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Identifikasi Hama dan Penyakit Pada Tanaman Anggrek Bulan (Phalaenopsis amabilis) by Ari Monawati, Desi Rhomadhoni, Nur Rokhimah Hanik

“…It is estimated that worldwide there are around 15,000-20,000 species of orchids with 900 genera (clans) that grow endemic to forests scattered in various countries. Of all orchid species in the world, 5,000 of them are in Indonesia. …”
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Aroma profile of two commercial truffle species from Yunnan and Sichuan, China: inter- and intraspecific variability and shared key compounds by Bin Lu, Jesús Perez-Moreno, Fengming Zhang, Andrea C. Rinaldi, Fuqiang Yu

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Mood Detection from Physical and Neurophysical Data Using Deep Learning Models by Zeynep Hilal Kilimci, Aykut Güven, Mitat Uysal, Selim Akyokus

“…Multinomial Naïve Bayes (MNB), Support Vector Regression (SVR), Decision Tree (DT), Random Forest (RF), and Decision Integration Strategy (DIS) are evaluated as conventional machine learning algorithms. …”
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Honoring the Afro-Colombian musical culture with the naming of Epipedobates currulao sp. nov. (Anura, Dendrobatidae), a frog from the Pacific rainforests by Mileidy Betancourth-Cundar, Juan Camilo Ríos-Orjuela, Andrew J. Crawford, David C. Cannatella, Rebecca D. Tarvin

“…This species inhabits lowland forests from 0–260 m a.s.l. This taxon differs from congeners by having a combination of bright yellow blotches in the dorsal anterior region of the thigh and upper arm, homogenous dark-brown dorsal coloration, and advertisement calls of long duration and many pulses. …”
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Reproductive and persistence strategy of the liverwort Arnellia fennica after the last glaciation in the area of disjunction in Central Europe (Polish Tatra Mountains, carpathians) by Piotr Górski, Monika Szczecińska, Jakub Sawicki

“…Within the Carpathians, it is only known from the Tatra Mountains (in Poland), where so far only four occurrences have been documented in the forest belt of the limestone part of the Western Tatras. …”
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Radiomics for differentiating adenocarcinoma and squamous cell carcinoma in non-small cell lung cancer beyond nodule morphology in chest CT by Minmini Selvam, Abjasree Sadanandan, Anupama Chandrasekharan, Sidharth Ramesh, Arunan Murali, Ganapathy Krishnamurthi

“…Lung nodules were classified using 13 machine-learning algorithms, including Linear Discriminant Analysis, Random Forest, AdaBoost, and eXtreme Gradient Boosting. The Multilayer Perceptron (MLP) Classifier with Rectified Linear Unit (ReLu) activation was the most accurate (83% accuracy) with 83% precision and 86% sensitivity in distinguishing SCC from adenocarcinoma. …”
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