An optimized data analytics pipeline for improving healthcare diagnosis using ensemble learning by Lomat Haider Chowdhury, Shaira Tabassum, Swakkhar Shatabda, Ashir Ahmed

“…Later, five state-of-the-art ensemble models for healthcare diagnosis were implemented along with a proposed ensemble machine learning model, KNN-XGBoost-SVM-Random Forest (KNN-X-SVM-R). The proposed model achieved an accuracy of 97.03% which supersedes all the other state-of-the-art models. …”
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Diversity and composition of vegetation and soil seed banks after sand dune restoration by oil mulching and plantations by Banafsheh Jalilian, Noredin Rostami, Mehdi Heydari, Mehrdad Kohzadian, Orsolya Valkó, Reza Omidipour

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The impact of spray-induced gene silencing on cereal phyllosphere microbiota by Poorva Sundararajan, Samrat Ghosh, Bekele Gelena Kelbessa, Stephen C. Whisson, Mukesh Dubey, Aakash Chawade, Ramesh Raju Vetukuri

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Developing clinical prognostic models to predict graft survival after renal transplantation: comparison of statistical and machine learning models by Getahun Mulugeta, Temesgen Zewotir, Awoke Seyoum Tegegne, Mahteme Bekele Muleta, Leja Hamza Juhar

“…Various models were evaluated, including Standard and penalized Cox models, Random Survival Forest, and Stochastic Gradient Boosting. Prognostic predictors were selected based on statistical significance and variable importance. …”
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Finite Element and Machine Learning-Based Prediction of Buckling Strength in Additively Manufactured Lattice Stiffened Panels by Saiaf Bin Rayhan, Md Mazedur Rahman, Jakiya Sultana, Szabolcs Szávai, Gyula Varga

“…Finally, the data samples collected from numerical outcomes were utilized to train four different machine learning models, namely multi-variable linear regression, polynomial regression, the random forest regressor and the K-nearest neighbor regressor. …”
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Heartwood/Sapwood Characteristics of <i>Populus euphratica</i> Oliv. Trunks and Their Relationship with Soil Physicochemical Properties in the Lower Tarim River, Northwest China by Tongyu Chen, Tayierjiang Aishan, Na Wang, Ümüt Halik, Shiyu Yao

“…This study examines the natural <i>Populus euphratica</i> Oliv. forest in the Arghan section of the lower Tarim River, comparing the heartwood and sapwood characteristics of <i>P. euphratica</i> at different distances from the river, as well as at varying trunk heights and diameters at breast height (DBH). …”
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Comparison of the efficacy and safety of bupropion versus aripiprazole augmentation in adults with treatment-resistant depression: a nationwide cohort study in South Korea by Dong Yun Lee, Rae Woong Park, Soo Min Jeon

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Proximate Composition and In Vitro Bioactive Properties of Leaf Extracts from Seven <i>Viola</i> Species by Guangnian Zeng, Xingfan Li, Chunbo Zhao, Yongkang Pang, Xiongfei Luo, Zhonghua Tang

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Addressing Label Noise in Colorectal Cancer Classification Using Cross-Entropy Loss and pLOF Methods With Stacking-Ensemble Technique by Ishrat Zahan Tani, Kah Ong Michael Goh, Md Nazmul Islam, Md Tarek Aziz, S. M. Hasan Mahmud, Dip Nandi

“…Fourth, we adopted a random forest–based recursive feature elimination (RF-RFE) feature selection method with various combinations of features to recursively select the most influential ones for accurate predictions. …”
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New Resinogalea species from Araucaria araucana resin in Chile and reclassification of the genus in the Cryptocaliciomycetidae by Felipe Balocchi, Irene Barnes, Michael J. Wingfield, Rodrigo Ahumada, Cobus M. Visagie

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Development and validation of the modified index of fragility in head and neck cancer surgery by Koorosh Semsar-Kazerooni, Keith Richardson, Véronique-Isabelle Forest, Alex Mlynarek, Michael P. Hier, Nader Sadeghi, Marco. A. Mascarella

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Ensemble machine learning models for lung cancer incidence risk prediction in the elderly: a retrospective longitudinal study by Songjing Chen, Sizhu Wu

“…For each subgroup, random forest, extreme gradient boosting, deep neural networks, support vector machine, multiple logistic regression and deep Q network (DQN) models were developed and validated. …”
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Evaluación del efecto de las temperaturas de almacenamiento sobre los parámetros de vigor en semillas de Neltuma caldenia Burkart by Marco Utello, Alexis Osmar Genero, Marcela Alejandra Demaestri

“…Los bosques de "caldén" en el Distrito del Caldén, región fitogeográfica del Espinal, se encuentran muy modificados por el efecto de la explotación forestal, desmontes, incendios y el pastoreo excesivo. …”
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Impacts of climate change on the suitable habitat of Angelica sinensis and analysis of its drivers in China by Shaoyang Xi, Xudong Guo, Xiaohui Ma, Ling Jin

“…Overlay analysis with 2020 land cover data indicated that 861,437 km² of arable and forest land are suitable for A. sinensis cultivation. …”
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AI predicting recurrence in non-muscle-invasive bladder cancer: systematic review with study strengths and weaknesses by Saram Abbas, Rishad Shafik, Naeem Soomro, Rakesh Heer, Rakesh Heer, Kabita Adhikari

“…., radiomics, clinical, histopathological, genomic) and types of ML models, such as neural networks, deep learning, and random forests. Each study was analysed for strengths, weaknesses, performance metrics, and limitations, with emphasis on generalisability, interpretability, and cost-effectiveness. …”
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A recurrence model for non-puerperal mastitis patients based on machine learning. by Gaosha Li, Qian Yu, Feng Dong, Zhaoxia Wu, Xijing Fan, Lingling Zhang, Ying Yu

“…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”
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From physical activity patterns to cognitive status: development and validation of novel digital biomarkers for cognitive assessment in older adults by Ling-Jie Fan, Feng-Yi Wang, Jun-Han Zhao, Jun-Jie Zhang, Yang-An Li, Jia Tang, Tao Lin, Quan Wei

“…We then developed explainable machine learning models, primarily random forest, optimized with hyperparameters, to predict individual cognitive function status. …”
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Assessment of grazing livestock balance on the Eastern Mongolian Plateau based on remote sensing monitoring and grassland carrying capacity evaluation by Menghan Li, Juanle Wang, Kai Li, Yaping Liu, Altansukh Ochir, Davaadorj Davaasuren

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Developing soil quality indices to investigate degradation impacts of different land use types in Northern Ethiopia by Araya Kahsay, Mitiku Haile, Girmay Gebresamuel, Muktar Mohammed

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Structure, Mechanical Performance, and Dimensional Stability of Radiata Pine (Pinus radiata D. Don) Scrimbers by Jinguang Wei, Fei Rao, Yuxiang Huang, Yahui Zhang, Yue Qi, Wenji Yu, Chung-Yun Hse

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