Seed Protein Content Estimation with Bench-Top Hyperspectral Imaging and Attentive Convolutional Neural Network Models by Imran Said, Vasit Sagan, Kyle T. Peterson, Haireti Alifu, Abuduwanli Maiwulanjiang, Abby Stylianou, Omar Al Akkad, Supria Sarkar, Noor Al Shakarji

“…Convolutional neural networks (CNNs) with attention mechanisms were proposed along with traditional machine learning models based on feature engineering including Random Forest (RF) and Support Vector Machine (SVM) regression for comparative analysis. …”
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Simulation and explanatory analysis of dissolved oxygen dynamics in Lake Ulansuhai, China by Fan Zhang, Xiaohong Shi, Shengnan Zhao, Ruonan Hao, Biao Sun, Guohua Li, Shihuan Wang, Hao Zhang

“…Study focus: After implementing the optimal noise reduction strategies based on wavelet transform for the high-frequency monitoring data, hybrid models coupling random forests, support vector machines, and artificial neural networks were employed to simulate the dissolved oxygen in the lake during both the open-water and ice-covered periods. …”
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Neonatal near Miss and Its Predictors among Neonates Delivered at Debretabor General Hospital, Northern Ethiopia; A Retrospective Analysis by Habtamu Abie Tassew, Fisseha Yetwale Kassie, Muhabaw Shumye Mihret

“…Both pragmatic and management criteria of definition of neonatal near miss were utilized. A systematic random sampling technique was used to select the cards of the study participants. …”
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Teaching communication skills to OTL-HNS residents: multisource feedback and simulated scenarios by Pier-Luc Beaudoin, Mathilde Labbé, Amanda Fanous, Meredith Young, Jamie Rappaport, Yoon Soo Park, John Manoukian, Lily H. P. Nguyen

“…There was no statistical difference in the mean ratings of performance across post-graduate year (PGY) level (p = 0.201). Results from the random-intercept regression indicated that, on average, a learner’s mean rating at baseline was 3.6/5 and increased significantly by 0.25 points per year (p < 0.05) as assessed by OTL-HNS staff members and peers. …”
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Prevalence of sudden unexpected death of infants and its subcategories in low- or middle-income countries: a systematic review protocol by Liesl Zühlke, David Coetzee, Mark Engel, Natasha R Rhoda, Eunice Turawa, Imen Ayouni, Shanaaz Mathews

“…Where possible, data on prevalence, incidence and subcategories will be pooled using a random effects meta-analysis to account for variability between estimates. …”
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Insights into the contribution of multiple factors on Ixodes ricinus abundance across Europe spanning 20 years using different machine learning algorithms by Samantha Lansdell, Abin Zorto, Misaki Seto, Edessa Negera, Saeed Sharif, Sally Cutler

“…Furthermore, using a Random Forest (RF) model across three clustering methods, we determined which features most significantly impacted upon I. ricinus abundance. …”
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Systematic review and bayesian network meta-analysis: comparative efficacy and safety of six commonly used biologic therapies for moderate-to-severe Crohn’s disease by Haohang Su, Haohang Su, Shengwei Xiao, Zhiqing Liang, Zhiqing Liang, Tianrong Xun, Jinfang Zhang, Jinfang Zhang, Xixiao Yang, Xixiao Yang

“…A random-effects model was performed with rankings according to the surface under cumulative ranking curve (SUCRA) probability. …”
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Patient education materials for non-specific low back pain and sciatica: a protocol for a systematic review and meta-analysis by Kris Aubrey-Bassler, Amanda Hall, Michelle Swab, Bradley Furlong, Andrea Pike, Holly Etchegary, Georgia Darmonkow

“…Risk of bias will be assessed using the PEDro scale, and the quality of evidence will be assessed with the Grades of Recommendation, Assessment, Development and Evaluation approach. A random-effects model will be used for each contrast, and results will be pooled if the participants, interventions, and outcomes are homogeneous. …”
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Novel Indices of Glucose Homeostasis Derived from Principal Component Analysis: Application for Metabolic Assessment in Pregnancy by Tina Stopp, Michael Feichtinger, Ingo Rosicky, Gülen Yerlikaya-Schatten, Johannes Ott, Hans Christian Egarter, Christian Schatten, Wolfgang Eppel, Peter Husslein, Martina Mittlböck, Andrea Tura, Christian S. Göbl

“…PCS1 to 3 assessed at early pregnancy were also associated with development of GDM, whereby random forest analysis revealed the highest variable importance for PCS1. …”
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Magnitude of fruit and vegetable consumption and its associated factors among patients with type 2 diabetes mellitus (T2DM) attending health services at selected health centers in... by Lelisa Worku, Burtukan Hussien, Teshome Bekele Elema, Taferi Atomsa Rekiti, Amana Ogatu Luke, Addisu Tadesse Sime

“…The sample comprised 285 patients with T2DM chosen by simple random sampling technique. Data collection was carried out via a structured questionnaire, followed by interviews and further analysed using SPSS V.25. …”
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Comparative assessment of empirical and hybrid machine learning models for estimating daily reference evapotranspiration in sub-humid and semi-arid climates by Siham Acharki, Ali Raza, Dinesh Kumar Vishwakarma, Mina Amharref, Abdes Samed Bernoussi, Sudhir Kumar Singh, Nadhir Al-Ansari, Ahmed Z. Dewidar, Ahmed A. Al-Othman, Mohamed A. Mattar

“…The ML models examined include Random Forest (RF), M5 Pruned (M5P), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), with hybrid combinations of RF-M5P, RF-XGBoost, RF-LightGBM, and XGBoost-LightGBM. …”
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Effect of Catheterization Time combined with Volume on Patients with Incomplete Bladder Emptying after Stroke by Huiying ZHANG, Xiuqin SHAO, Tianzi ZOU, Xiaoyue LI, Shuang QUAN, Tongzhou MI

“…Objective:To observe the effect of catheterization time combined with catheterization volume on patients with incomplete bladder emptying (IBE) after stroke.Methods:A total of 62 patients with IBE after stroke were divided into the control group (<italic>n</italic>=30) and the observation group (<italic>n</italic>=32) respectively, in the first affiliated hospital of Nanchang University from June to December 2017, according to the random number table method. The control group was given routine rehabilitation treatment such as transcutaneous nerve stimulation, acupuncture, bladder function retraining, and at the same time, the patients were given time-type intermittent catheterization once every 4-8 hours. …”
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Construction of a prognostic prediction model for colorectal cancer based on 5-year clinical follow-up data by Boao Xiao, Min Yang, Yao Meng, Weimin Wang, Yuan Chen, Chenglong Yu, Longlong Bai, Lishun Xiao, Yansu Chen

“…A modeling dataset containing 73 characteristic variables was established by collecting demographic information, clinical blood test indicators, histopathological results, and additional treatment-related information. Decision tree, random forest, support vector machine, and extreme gradient boosting (XGBoost) models were selected for modeling based on the features identified through recursive feature elimination (RFE). …”
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Research on Risk Prediction of Condiments Based on Gray Correlation Analysis – Deep Neural Networks by Miao Zhang, Yiran Wan, Haiyang He, Yuanjia Hu, Changhong Zhang, Jingyuan Nie, Yanlei Wu, Kaiying Deng, Xun Lei, Xianliang Huang

“…Then, three machine learning models, Deep Neural Network (DNN), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost), were used to predict the comprehensive risk values. …”
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Development of a stable eukaryotic strain producing fully human monoclonal antibody on the basis of the human antibody against ectromelia virus by A. L. Matveev, Ya. A. Khlusevich, I. K. Baykov, I. V.  Babkin, E. P. Goncharova, V. V. Morozova, N. V. Tikunova

“…To develop the producing strain, random integration of the plasmid containing the gene encoding the target protein into the genome of the host cells is commonly used. …”
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Serological markers of exocrine pancreatic function are differentially informative for distinguishing individuals progressing to type 1 diabetes by Desmond Schatz, Laura Jacobsen, Todd M Brusko, Michael J Haller, Mark Atkinson, MacKenzie D Williams, Catherine Ramsey Grace, Amanda L Posgai, Kieran M McGrail, Maigan A Brusko, Rhonda Bacher, Clive H Wasserfall

“…We collectively evaluated seven such biomarkers, combined with islet autoantibodies (AAb) and genetic risk score (GRS2), for their utility in predicting AAb/T1D status.Research design and methods Cross-sectional serum samples (n=154 T1D, n=56 1AAb+, n=77 ≥2AAb+, n=256 AAb−) were assessed for IGF1, IGF2, adiponectin, leptin, amylase, lipase, and trypsinogen (n=543, age range 2.7–30.0 years) using random forest modeling.Results GRS2, age, lipase, trypsinogen, and AAb against ZnT8, GAD65, and insulin were the most informative markers. …”
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A Comparison of Classification Algorithms for Predicting Dis-tinctive Characteristics in Fine Aroma Cocoa Flowers Using WE-KA Modeler by Daniel Tineo, Yuriko S. Murillo, Mercedes Marín, Darwin Gomez, Victor H. Taboada, Malluri Goñas, Lenin Quiñones Huatangari

“…Three attribute evaluators (InfoGainAttributeEval, CorrelationAttributeEval and GainRatioAttributeEval), and six algorithms (Naive Bayes, Multinomial Logistic Regression, J48, Random Forest, LTM and Simple Logistic) were employed in this study. …”
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Clinical outcomes and adverse events of Hedgehog pathway inhibitors for advanced basal cell carcinoma patients: A systematic review and meta-analysis by Suvijak Untaaveesup, Wichapol Dendumrongsup, Pornteera Srichana, Chanamon Pongphaew, Gynna Techataweewan, Kanmanee Viratkapan, Nichanant Nampipat, Ben Ponvilawan, Chayanis Kositamongkol, Walaiorn Pratchyapruit, Pochamana Phisalprapa

“…Pooled objective response rates (ORRs) and 95% confidence intervals (CIs) were calculated using inverse variance random-effects models. Results: The analysis comprised 16 studies, including 14 retrospective cohort studies, one prospective cohort study, and one randomized controlled trial, with 1689 participants. …”
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Effect of tropical climates on the quality of commonly used antibiotics: the protocol for a systematic review and meta-analysis by Johnstone Thitiri, Moses Ngari, Christina W Obiero, James A Berkley, Tsegaye Melaku, Sultan Suleman, Gemmechu Hasen, Sileshi Belew, Jimmy Shangala

“…The available evidence for the poor quality of commonly used antibiotics is summarised by the type of diagnosis, type of drug and region. Meta-analysis using random effects will be performed using RevMan software to determine the pooled effects of environmental exposures. …”
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Impact of measles vaccination strategies on vaccination rates in low-income and middle-income countries: a systematic review and meta-analysis by Andrew Hayen, Kiddus Yitbarek, Mirkuzie Woldie, Firew Tekle Bobo, Jane Frawley, Abela Mahimbo, Meru Sheel

“…We predetermined measles vaccination coverage and timeliness as the primary outcomes, with hospitalisation and mortality as secondary outcomes. A random-effects model was employed for the meta-analysis.Results We identified 44 articles, of which 14 were included in the meta-analysis. …”
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