High genetic gains in wood volume and fecundity can be both achieved by direct selection in half-sib families of Pinus yunnanensis Franch by Chengjie Gao, Zhongmu Li, Jin Li, Kai Cui

“…Using structural equation modeling and “random forest” analysis, we identified key predictors of cone production and trunk straightness and assessed trait interrelationships. …”
Get full text

Integrated Machine Learning Approaches for Landslide Susceptibility Mapping Along the Pakistan–China Karakoram Highway by Mohib Ullah, Haijun Qiu, Wenchao Huangfu, Dongdong Yang, Yingdong Wei, Bingzhe Tang

“…To address this, this study assessed the performance of six machine learning models, including Convolutional Neural Networks (CNNs), Random Forest (RF), Categorical Boosting (CatBoost), their CNN-based hybrid models (CNN+RF and CNN+CatBoost), and a Stacking Ensemble (SE) combining CNN, RF, and CatBoost in mapping landslide susceptibility along the Karakoram Highway in northern Pakistan. …”
Get full text

Multimodal feature fusion-based graph convolutional networks for Alzheimer's disease stage classification using F-18 florbetaben brain PET images and clinical indicators. by Gyu-Bin Lee, Young-Jin Jeong, Do-Young Kang, Hyun-Jin Yun, Min Yoon

“…The effectiveness of GCN was demonstrated through comparisons with the support vector machine, random forest, and multilayer perceptron across four classification tasks (normal control (NC) vs. …”
Get full text

Advanced automated machine learning framework for photovoltaic power output prediction using environmental parameters and SHAP interpretability by Muhammad Paend Bakht, Mohd Norzali Haji Mohd, Babul Salam KSM Kader Ibrahim, Nuzhat Khan, Usman Ullah Sheikh, Ab Al-Hadi Ab Rahman

“…The top four performing models, achieving the highest predictive accuracies, were identified as Extra Tree (91% accuracy), Random Forest (85%), XGBoost (75%), and Decision Tree (68%) for further analysis. …”
Get full text

Maximizing udder health through a selection index: a focus on udder traits in Italian Mediterranean Buffaloes by Johanna Ramírez Díaz, Roberta Cimmino, Rossi Dario, Zullo Gianluigi, Neglia Gianluca, Altieri Damiano, Mayra Gómez, Stefano Biffani, Giuseppe Campanile

“…A multitrait animal model that included CG (herd-year-calving season), calving month, and parity as fixed effects, and the animal as a random effect was used. The estimated heritability for MP and MSCS150 were 0.391 and 0.134, respectively, and varied between 0.11 and 0.23 for UC traits. …”
Get full text

Correlation of diabetes and adverse outcomes in hospitalized COVID-19 patients admitted to a tertiary hospital in China during a small-scale COVID-19 outbreak by Yu Li, Guanni Li, Jiahong Li, Zirui Luo, Yaxuan Lin, Ning Lan, Xiaodan Zhang

“…Compared with the survivors, non-survived COVID-19 patients with diabetes had worse diabetes control indicators, with random blood glucose increased by 3.58 mmol/L (p < 0.05), and fasting blood glucose increased by 2.77 mmol/L (p < 0.01). …”
Get full text

Time to Reach Full Enteral Feeding and Its Predictors among Very Low Birth Weight Neonates Admitted in the Neonatal Intensive Care Unit: A Follow-Up Cohort Study by Belay Alemayehu Getahun, Sileshi Mulatu, Hailemariam Mekonnen Workie

“…Samples were selected through a computer-generated simple random sampling method, and the data were entered into Epi data version 4.6 and then exported to STATA version 16 for analysis. …”
Get full text

Association of Depression with Uncontrolled Hypertension in Primary Care Setting: A Cross-Sectional Study in Less-Developed Northwest China by Lin Wang, Nanfang Li, Mulalibieke Heizhati, Mei Li, Zhikang Yang, Zhongrong Wang, Reyila Abudereyimu

“…We used a stratified multistage random sampling method to obtain 1856 hypertensives subjects aged ≥18 years among primary care setting in Xinjiang, Northwest China, between April and October 2019. …”
Get full text

Application of deep learning and feature selection technique on external root resorption identification on CBCT images by Nor Hidayah Reduwan, Azwatee Abdul Aziz, Roziana Mohd Razi, Erma Rahayu Mohd Faizal Abdullah, Seyed Matin Mazloom Nezhad, Meghna Gohain, Norliza Ibrahim

“…The performance of four DLMs including Random Forest (RF) + Visual Geometry Group 16 (VGG), RF + EfficienNetB4 (EFNET), Support Vector Machine (SVM) + VGG, and SVM + EFNET) and four hybrid models (DLM + FST: (i) FS + RF + VGG, (ii) FS + RF + EFNET, (iii) FS + SVM + VGG and (iv) FS + SVM + EFNET) was compared. …”
Get full text

Value of transabdominal ultrasonography for diagnosing functional constipation in children: a systematic review and meta-analysis by Duc Long Tran, Phu Nguyen Trong Tran, Paweena Susantitaphong, Phichayut Phinyo, Palittiya Sintusek

“…Metaanalyses were performed using random-effects models to calculate the weighted mean differences (MDs) in RD and anterior wall thickness. …”
Get full text

THE POTENTIAL OF POLLARD AND RICE BRAN WITH FRACTIONATION PROCESS AS RAW MATERIALS FOR HIGH FIBER PROCESSED FOOD by Ainun Nafisah, Nahrowi Nahrowi

“…The experimental design used was CRD (Completely Random Design) Factorial 2 × 3 × 3 for physical test data. …”
Get full text

Predictors of client satisfaction with family planning services in Ethiopia: a systematic review and meta-analysis by Yeshiwas Ayale Ferede, Worku Chekol Tassew, Agerie Mengistie Zeleke

“…If significant heterogeneity was found across the included studies, a random effects model was used to assess the factors influencing client satisfaction with family planning services. …”
Get full text

Simulation of the effect of absorption by atmospheric water vapor on the results of non-contact temperature measurements by A. B. Ionov, N. S. Chernysheva, B. P. Ionov, M. A. Ryabova

“…On the basis of the simulation performed using the MATLAB system and the HITRAN molecular spectroscopy database, the values of random and systematic errors are calculated for four measurement situations typical of industrial conditions that differ in the level of absorption by water vapor. …”
Get full text

Diabetes and Cataracts Development—Characteristics, Subtypes and Predictive Modeling Using Machine Learning in Romanian Patients: A Cross-Sectional Study by Adriana Ivanescu, Simona Popescu, Adina Braha, Bogdan Timar, Teodora Sorescu, Sandra Lazar, Romulus Timar, Laura Gaita

“…With the use of machine learning, the patients were assessed and categorized as having one of the three main types of cataracts: cortical (CC), nuclear (NS), and posterior subcapsular (PSC). A Random Forest Classification algorithm was employed to predict the incidence of different associations of cataracts (1, 2, or 3 types). …”
Get full text

Chronic effects of school physical activity on cognitive performance in youngs: a systematic review protocol by Fernando William Flores Silva, Ricardo Martins, Rochelle Rocha Costa, Carlos Cristi-Montero, Júlio Brugnara Mello

“…The effect size will be expressed as Cohens’ and presented as standardized mean differences and calculations will be performed using random-effects models. Statistical heterogeneity will be evaluated by Cochran’s Q statistic and the I² inconsistency test. …”
Get full text

Soil carbon-food synergy: sizable contributions of small-scale farmers by Toshichika Iizumi, Nanae Hosokawa, Rota Wagai

“…Here, we present a global analysis of small-scale farmers’ contributions to the potential of additional SOC stocks and the associated increase in crop production. Methods We applied random forest machine learning models to global gridded datasets on crop yield (wheat, maize, rice, soybean, sorghum and millet), soil, climate and agronomic management practices from the 2000s (n = 1808 to 8123). …”
Get full text

Basal metabolic rate correlates with excess postexercise oxygen consumption across different intensities by Shu-Chun Huang, Kuan-Hung Chen, Watson Hua-Sheng Tseng, Lan-Yan Yang, Ching-Chung Hsiao, Yi-Chung Fang, Chen-Hung Lee

“…The CWR tests were conducted at low, moderate, and high intensities in random order. After each CWR test, the EPOC and the ratio of EPOC to oxygen consumption during exercise (OC) were calculated. …”
Get full text

Assessing the Direct Impact of Typhoons on Vegetation Canopy Structure and Photosynthesis by Yaoyao Zheng, Simin Zhan, Zaichun Zhu, Sen Cao, Jiana Chen, Pengjun Zhao, Weimin Wang, Ranga B. Myneni

“…This study proposes a novel framework for quantifying typhoons’ immediate and long-term impacts on vegetation canopy structure and photosynthesis. We developed random forest models based on satellite-observed leaf area index (LAI) and environmental data during typhoon-free periods to simulate LAI under non-typhoon conditions. …”
Get full text

Genome wide landscaping of copy number variations for horse inter-breed variability by Nitesh Kumar Sharma, Prashant Singh, Bibek Saha, Anuradha Bhardwaj, Mir Asif Iquebal, Yash Pal, Varij Nayan, Sarika Jaiswal, Shiv Kumar Giri, Ram Avatar Legha, T. K. Bhattacharya, Dinesh Kumar, Anil Rai

“…An Equine CNVs database, EqCNVdb (http://backlin.cabgrid.res.in/eqcnvdb/) was developed which catalogues detailed information on the horse CNVs, CNVRs and gene content within CNVRs. Also, three random CNVRs were validated with real-time polymerase chain reaction. …”
Get full text

Biomarkers predicting postoperative adverse outcomes in children with congenital heart disease: a systematic review and meta-analysis by Shifan Zhou, Shifan Zhou, Lu Liu, Xiaochuang Jin, Daniel Dorikun, Songfeng Ma

“…Standard deviation or odds ratio (OR) with 95% confidence interval (95% CI) were extracted. A random-effects model synthesized SMDs or ORs with 95% CIs. …”
Get full text