Practice and factors associated with sunlight exposure of infants among mothers in Ethiopia: a systematic review and meta-analysis by Shambel Dessale Asmamaw, Tibebu Habte Zewde, Abiel Teshome, Esayas Nigussie

“…The pooled prevalence with a 95% confidence interval (CI) of the meta-analysis utilizing the random effect model was displayed using forest plots, and adjusted odds ratio (AOR) was utilized to quantify the association. …”
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A Study on Canopy Volume Measurement Model for Fruit Tree Application Based on LiDAR Point Cloud by Na Guo, Ning Xu, Jianming Kang, Guohai Zhang, Qingshan Meng, Mengmeng Niu, Wenxuan Wu, Xingguo Zhang

“…For feature selection, a random forest-based recursive feature elimination method with cross-validation was employed to filter 10 features. …”
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Investigating the effects of hyperparameter sensitivity on machine learning algorithms for PV forecasting by Ehtsham Muhammad, Rotilio Marianna, Cucchiella Federica, Di Giovanni Gianni, Schettini Domenico

“…Four state-of-the-art ML models, namely Decision Trees (DT), Random Forest (RF), K-Nearest Neighbors (KNN), and Support Vector Regression (SVR) were investigated. …”
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Formulated citrus peel extract gold lotion improves cognitive and functional recovery from traumatic brain injury (TBI) in rats by Cheng Guang, Yue Zhiwei, Wang Liwen, Miyauchi Yutaka, Suzawa Michiko, Li Shiming, Ho Chi‐Tang, Zhao Hui, Chen Naiyao

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Prediction of successful weaning from renal replacement therapy in critically ill patients based on machine learning by Qiqiang Liang, Xin Xu, Shuo Ding, Jin Wu, Man Huang

“…Next, we demonstrated that machine learning models, especially Random Forest and XGBoost, achieving an AUROC of 0.95. The XGBoost model exhibited superior accuracy, yielding an AUROC of 0.849.Conclusion High-risk factors for unsuccessful RRT weaning in severe AKI patients include prolonged RRT duration. …”
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A Hybrid Fuzzy Wavelet Neural Network Model with Self-Adapted Fuzzy c-Means Clustering and Genetic Algorithm for Water Quality Prediction in Rivers by Mingzhi Huang, Di Tian, Hongbin Liu, Chao Zhang, Xiaohui Yi, Jiannan Cai, Jujun Ruan, Tao Zhang, Shaofei Kong, Guangguo Ying

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Soil data from the Barbastro-Balaguer gypsum belt, NE SpainMendeley Data by Juan Herrero, María Tierra, Carmen Castañeda

“…The chesas have attracted the attention of botanists [6–8], foresters [9,10], and soil hydrophysical properties researchers [11]. …”
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Tabla de volumen comercial para teca clonal en diferentes índices de sitio en la Zona Norte de Costa Rica by Katherine Barrantes-Madrigal, Rafael Murillo-Cruz, Carlos Ávila-Arias, William Fonseca-González, Ana Isabel Barquero-Elizondo

“… [Introducción]: Es necesario cuantificar y predecir con confiabilidad el volumen de madera para facilitar la gestión de la producción forestal. [Objetivo]: Elaborar tablas de volumen comercial a partir de la selección de modelos matemáticos en distintas calidades de sitio, para plantaciones clonales de Tectona grandis L.f. …”
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Development and validation of an explainable machine learning prediction model of hemorrhagic transformation after intravenous thrombolysis in stroke by Yanan Lin, Yan Li, Yayin Luo, Jie Han

“…We utilized the Random Forest (RF), Multilayer Perceptron (MLP), Adaptive Boosting (AdaBoost), and Gaussian Naive Bayes (GauNB) algorithms to develop ML-HT models. …”
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Effect of short inter-pregnancy interval on perinatal and maternal outcomes among pregnant women in SSA 2023: Systematic review and meta-analysis. by Fentahun Yenealem Beyene, Kihinetu Gelaye Wudineh, Simachew Animen Bantie, Azimeraw Arega Tesfu

“…The results are presented using texts, tables and forest plots with measures of effect and 95% confidence interval.…”
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Evaluating the Impact of Data Transformation Techniques on the Performance and Interpretability of Software Defect Prediction Models by Yu Zhao, Zhiqiu Huang, Lina Gong, Yi Zhu, Qiao Yu, Yuxiang Gao

“…Through empirical research on (i) six classification techniques (random forest, decision tree, logistic regression, Naive Bayes, K-nearest neighbors, and multilayer perceptron), (ii) six performance evaluation indicators (Accuracy, Precision, Recall, F1, MCC, and AUC), (iii) two interpretable methods (permutation and SHAP), (iv) two feature importance measures (Top-k feature rank overlap and difference), and (v) three datasets (Promise, Relink, and AEEEM), our results show that the data transformation methods can significantly improve the performance of the SDP models and greatly affect the variation of the most important features. …”
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Diagnosis Osteoporosis Risk: Using Machine Learning Algorithms Among Fasa Adults Cohort Study (FACS) by Saghar Tabib, Seyed Danial Alizadeh, Aref Andishgar, Babak Pezeshki, Omid Keshavarzian, Reza Tabrizi

“…Methods We analysed the data related to osteoporosis risk factors obtained from the Fasa Adults Cohort Study in eight ML methods, including logistic regression (LR), baseline LR, decision tree classifiers (DT), support vector classifiers (SVC), random forest classifiers (RF), linear discriminant analysis (LDA), K nearest neighbour classifiers (KNN) and extreme gradient boosting (XGB). …”
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Influence of food availability on the diet and activity budget of two western lowland gorilla (Gorilla gorilla gorilla) groups of differing size in the Dzanga-Ndoki National Park,... by Terence Fuh Neba, Giuseppe Donati, Angelique Todd, Shelly Masi

“…Such flexibility may better allow WLG groups to track ripe fruits when available but, unlike sympatric chimpanzees, switch to more herbivorous diets when necessary, adjusting activity budgets accordingly ; WLGs thus may be considered more resilient faced with environmental change such as forest degradation.…”
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Retrospective cohort study based on the MIMIC-IV database: analysis of factors influencing all-cause mortality at 30 days, 90 days, 1 year, and 3 years in patients with different t... by Xuehui Fan, Jing Xu, Ruixue Ye, Qiu Zhang, Yulong Wang

“…Covariates included electrolyte levels, kidney function, organ function scores, and comorbidities. Random forest and gradient boosting tree models were employed for data analysis to assess mortality risk.ResultsKaplan–Meier survival analysis showed that ischemic stroke patients had the highest 30-day mortality rate at 8.5%, with only 20% 1-year survival. …”
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Molecular Characterization and Clinical Characteristics of m5C-Based RNA Methylation in Spinal Cord Injury: Validated by qPCR by Liang Cao, Wen Jun Pi, Qiang Zhang, Qing Li

“…We constructed a “gene signature” of m5C-based regulators of RNA modification to predict the prognosis of SCI using least absolute shrinkage and selection operator regression and random-forest strategy. We found that the m5C-related genes, deoxyribonucleic acid (DNA) methyltransferase1 (Dnmt1), methyl-CpG binding domain protein 2 (Mbd2), ubiquitin-like with PHD and ring finger domains 1 (Uhrf1), uracil-N-glycosylase (Ung), and zinc finger and BTB(brica-brac, tramtrack, and broad) domain containing 38 (Zbtb38) had high expression, and zinc finger and BTB domain containing 4 (Zbtb4) had low expression in SCI. …”
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Temporal and Spatial Characteristics and Influencing Factors of Carbon Storage in Black Soil Area Under Topographic Gradient by Zhaoxue Gai, Wenlu Zheng, Bonoua Faye, Hongyan Wang, Guoming Du

“…Therefore, this study emphasizes the importance of implementing policies that convert farmland to forests and wetlands and promote the green transformation of agriculture.…”
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Genome-wide identification of CAMTA gene family in teak (Tectona grandis) and functional characterization of TgCAMTA1 and TgCAMTA3 in cold tolerance by Wenlong Zhou, Jian Du, Runjie Jiao, Xianbang Wang, Tiansong Fang, Guihua Huang

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Quantitative Physiologic MRI Combined with Feature Engineering for Developing Machine Learning-Based Prediction Models to Distinguish Glioblastomas from Single Brain Metastases by Seyyed Ali Hosseini, Stijn Servaes, Brandon Hall, Sourav Bhaduri, Archith Rajan, Pedro Rosa-Neto, Steven Brem, Laurie A. Loevner, Suyash Mohan, Sanjeev Chawla

“…<b>Results</b>: A random forest classifier with ANOVA F-value feature selection algorithm using both interacting and non-interacting features provided the best diagnostic performance in distinguishing GBMs from BMs with an area under the ROC curve of 92.67%, a classification accuracy of 87.8%, a sensitivity of 73.64% and a specificity of 97.5%. …”
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Soil preferential flow dynamics in the southern drylands of India—a watershed based approach by Pushpanjali, K. S. Reddy, Ashish S. Dhimate, K. Karthikeyan, Josily Samuel, A. G. K. Reddy, N. Ravi Kumar, K. V. Rao, Prabhat Kumar Pankaj, Jagriti Rohit, Manoranjan Kumar, V. K. Singh

“…Brilliant blue tracer experiments were conducted at selected sites within the Hayathnagar watershed to assess soil preferential flow and investigate the subsurface movement of water across three land uses (cropped, fallow, and forest) under varying elevations. Vertical profile images were captured using a Canon EOS 1300D digital camera, producing high-resolution images (5184 × 3456 pixels). …”
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Cardiac computer tomography-derived radiomics in assessing myocardial characteristics at the connection between the left atrial appendage and the left atrium in atrial fibrillation... by Xiao-Xuan Wei, Cai-Ying Li, Hai-Qing Yang, Peng Song, Bai-Lin Wu, Fang-Hua Zhu, Jing Hu, Xiao-Yu Xu, Xin Tian

“…The radiomics model was built by extracting radiomic features of the myocardial tissue using Pyradiomics, and employing Least absolute shrinkage and selection operator (LASSO) method for feature selection, combining random forest with support vector machine (SVM) classifier.ResultsThere were 82 cases in the AF group [44 males, 65.00 (59, 70)], and 56 cases in the control group (21 males, 61.09 ± 7.18). …”
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