Spatiotemporal Variability of Channel Roughness and its Substantial Impacts on Flood Modeling Errors by Md Abdullah Al Mehedi, Shah Saki, Krutikkumar Patel, Chaopeng Shen, Sagy Cohen, Virginia Smith, Adnan Rajib, Emmanouil Anagnostou, Tadd Bindas, Kathryn Lawson

“…These large, diverse observations allowed training of a Random Forest (RF) model capable of predicting n (or alternative parameters) at high accuracy (Nash Sutcliffe model efficiency >0.7) in space and time. …”
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Glaucoma detection and staging from visual field images using machine learning techniques. by Nahida Akter, Jack Gordon, Sherry Li, Mikki Poon, Stuart Perry, John Fletcher, Thomas Chan, Andrew White, Maitreyee Roy

“…Among the ML models, the random forest (RF) classifier performed best with an F1 score of 96%.…”
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The effect of post-exercise heat exposure (passive heat acclimation) on endurance exercise performance: a systematic review and meta-analysis by Thomas P. J. Solomon, Matthew J. Laye

“…To determine the effect of post-exercise heat exposure, between-group ratio of means or standardized mean differences (SMD) were calculated for each outcome and weighted by the inverse of their variance to calculate an overall effect estimate (ratio of mean or Hedges’g) in a random effects meta-analysis, with 95% confidence intervals (CI) and prediction intervals (PI). …”
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The Effect of Innovative Technology Benefits and E-Commerce Using Motivations on Customer Experience and Customer Information by Zahra Bigdelou, Alireza Rousta, Farzad Asayesh

“…The sampling method was random sampling.Findings: The results showed that the usefulness of technology positively affects the user's sense of satisfaction. …”
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Alpine vegetation community patterns in the Khumbu region, Nepalese Himalaya by Ruolin Leng, Stephan Harrison, Elizabeth A. Byers, Mahesh Magar, Harkrei Rai, Ram Raj Rijal, Karen Anderson

“…Field data captured during in situ surveys in the Gokyo valley, Nepal, were used to drive and then test a random forest classifier. Grassy meadows and dwarf shrubs belonging to the Rhododendron and Juniperus families dominate the ecology of the alpine zone in this region, so we created three vegetation classes for mapping indicative major plant communities dominated by these species. …”
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The effects of interaction between smoking and abdominal obesity on pre-diabetes mellitus by Huali Xiong, Peng Zhao, Fengxun Ma, Dayi Tang, Daiqiang Liu

“…The data was obtained from a cross-sectional survey conducted using a two stage random sampling method around Rongchang district in ChongQing municipality southwest of China in 2022. …”
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Burden and Determinant of Inadequate Dietary Diversity among Pregnant Women in Ethiopia: A Systematic Review and Meta-Analysis by Hagos Degefa Hidru, Meresa Berwo Mengesha, Yared Hailesilassie, Fissaha Tekulu Welay

“…Studies were retrieved from selected electronic databases, including PubMed, Cochrane Library, and Google Scholar. Random-effects model meta-analysis was used to estimate the pooled burden of inadequate dietary diversity and its determinants at a 95% confidence interval with its respective odds ratio (OR) using statistical R-software version 3.6.1. …”
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Proportion and Associated Factors of Low Vision among Adult Patients Attending at University of Gondar Tertiary Eye Care and Training Center, Gondar Town, Ethiopia by Melkamu Temeselew Tegegn, Gizachew Tilahun Belete, Ayanaw Tsega Ferede, Aragaw Kegne Assaye

“…A hospital-based cross-sectional study was conducted on 727 study participants with a systematic random sampling technique from April 18 to May 16, 2019. …”
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Robust Next-Day Scheduling of PV Generation Sources Supplying a Standalone DC Microgrid via a Semi-Definite Programming Model by Walter Gil-Gonzalez, Oscar Danilo Montoya, Luis F. Grisales-Norena, Fabio Andrade

“…Evaluating a 27-bus standalone DC microgrid, the SDP model outperforms random-based algorithms by achieving global optima in both objectives. …”
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Incidence and predictors of mortality among HIV positive children on anti-retroviral therapy in the selected health facilities of West Wollega Zone, Western Ethiopia: Retrospective... by Gelane Gurmu, Emiru Merdassa, Gemechu Tiruneh, Keneni Efrem, Firezer Belay, Lalisa Mekonnen, Jira Wakoya Feyisa, Matiyos Lema, Adisu Tafari Shama, Markos Desalegn

“…<h4>Methods</h4>A retrospective cohort study design was conducted. A simple random sampling method was employed to select 286 children living with HIV who started ART from 01 January 2012 to 31 October 2021. …”
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Effect of Hot and Cold Chinese Medicine Whirlpool Bath Combined with Motor Control Training on Patients with Shoulder-Hand Syndrome after Stroke by ZHANG Yuming, ZHANG Xiufang, CHEN Jie, LI Ning, ZHANG Xiaolin, ZHANG Ming

“…ObjectiveTo observe the effect of hot and cold Chinese medicine whirlpool bath combined with motor control training on patients with shoulder-hand syndrome (SHS) after stroke.MethodsA total of 40 patients with SHS after stroke in the Xuzhou Rehabilitation Hospital and Xuzhou Central Hospital from January to December 2020 were randomly divided into control group and observation group according to random number table method, with 20 cases in each group. …”
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Development and validation of an EHR-based risk prediction model for geriatric patients undergoing urgent and emergency surgery by Edward N. Yap, Jie Huang, Joshua Chiu, Robert W. Chang, Bradley Cohn, Judith C. F. Hwang, Mary Reed

“…Patients’ EHR-based clinical history, vital signs, labs, and demographics were included in logistic regression, LASSO, decision tree, Random Forest, and XGBoost models. Area under the receiver operating characteristics curve (AUCROC) was used to compare model performance. …”
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Golden Eagle in Karatau and Chu-Ili Mountains (Kazakhstan) and Assessment of Risks to its Populations from Developing Wind Energy by Igor V. Karyakin, Kirill I. Knizhov, Elvira G. Nikolenko, Elena P. Shnayder, Genriyetta I. Pulikova, Alyona G. Kaptyonkina

“…During the work, we modelled the distribution of the Golden Eagle in Karatau and the Chu-Ili Mountains using the Random Forest image classification method, calculated its numbers in this area and assessed the threats to its breeding groups from both existing and prospective WPPs. …”
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Factors Associated with Gestational Diabetes Mellitus: A Meta-Analysis by Yu Zhang, Cheng-Ming Xiao, Yan Zhang, Qiong Chen, Xiao-Qin Zhang, Xue-Feng Li, Ru-Yue Shao, Yi-Meng Gao

“…Pooled odds ratios (ORs) were calculated using fixed- or random-effects models. 103 studies involving 1,826,454 pregnant women were identified. …”
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Machine learning assisted radiomics in predicting postoperative occurrence of deep venous thrombosis in patients with gastric cancer by Yuan Zeng, Yuhao Chen, Dandan Zhu, Jun Xu, Xiangting Zhang, Huiya Ying, Xian Song, Ruoru Zhou, Yixiao Wang, Fujun Yu

“…Four machine learning algorithms, known as random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM) and naive Bayes (NB), were used to develop models for predicting the risk of lower extremity DVT occurrence in GC patients. …”
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Multimedia: multimodal mediation analysis of microbiome data by Hanying Jiang, Xinran Miao, Margaret W. Thairu, Mara Beebe, Dan W. Grupe, Richard J. Davidson, Jo Handelsman, Kris Sankaran

“…The software includes modules for regularized linear, compositional, random forest, hierarchical, and hurdle modeling, making it well-suited to microbiome data. …”
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Petrophysical Regression regarding Porosity, Permeability, and Water Saturation Driven by Logging-Based Ensemble and Transfer Learnings: A Case Study of Sandy-Mud Reservoirs by Shenghan Zhang, Yufeng Gu, Yinshan Gao, Xinxing Wang, Daoyong Zhang, Liming Zhou

“…Additionally, to highlight the validating effect, three sophisticated predictors, including k-nearest neighbors (KNN), support vector regression (SVR), and random forest (RF), are introduced as competitors to implement a contrast. …”
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Combined Liver Stiffness and Α-fetoprotein Further beyond the Sustained Virologic Response Visit as Predictors of Long-Term Liver-Related Events in Patients with Chronic Hepatitis... by Sheng-Hung Chen, Hsueh-Chou Lai, Wen-Pang Su, Jung-Ta Kao, Po-Heng Chuang, Wei-Fan Hsu, Hung-Wei Wang, Tsung-Lin Hsieh, Hung-Yao Chen, Cheng-Yuan Peng

“…Methods. Cox regression and random forest models identified the key factors, including longitudinal LS and noninvasive test results, that could predict LREs, including hepatocellular carcinoma, during prespecified follow-ups from 2010 to 2021. …”
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Predicting local control of brain metastases after stereotactic radiotherapy with clinical, radiomics and deep learning features by Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn

“…Radiomics features were extracted using the Python radiomics feature extractor and DL features were obtained using a 3D ResNet model. A Random Forest machine learning algorithm was employed to train four models using: (1) clinical features only; (2) clinical and radiomics features; (3) clinical and DL features; and (4) clinical, radiomics, and DL features. …”
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Effect of exercise training on cardiac autonomic function in type 2 diabetes mellitus: a systematic review and meta-analysis by Sohini Raje, G Arun Maiya, Padmakumar R, Mukund A. Prabhu, Krishnananda Nayak, Shivashankara KN, BA Shastry, Megha Nataraj

“…The meta-analysis was conducted using RevMan 5.4.1, using the random effects model, and appropriate tests for heterogeneity. …”
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