A novel methodological approach to SaaS churn prediction using whale optimization algorithm. by Muhammed Kotan, Ömer Faruk Seymen, Levent Çallı, Sena Kasım, Burcu Çarklı Yavuz, Tijen Över Özçelik

“…The scarcity of research on customer churn models in SaaS, particularly regarding diverse feature selection methods and predictive algorithms, highlights a significant gap. …”
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Altered neural avalanche spreading in people with drug-resistant epilepsy✰ by B.M. Sancetta, M.A.G. Matarrese, L. Ricci, J. Lanzone, G. Lippa, M. Nesta, F. Zappasodi, M. Brunetti, V. Di Lazzaro, M. Tombini, G. Assenza

“…Logistic regression was performed to test and compare the ability of graph theory metrics on ATM and clinical features to correctly discriminate the PwE group according to the clinical outcome (DRE or non-DRE). …”
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A tri-light warning system for hospitalized COVID-19 patients: Credibility-based risk stratification for future pandemic preparedness by Chuanjun Xu, Qinmei Xu, Li Liu, Mu Zhou, Zijian Xing, Zhen Zhou, Danyang Ren, Changsheng Zhou, Longjiang Zhang, Xiao Li, Xianghao Zhan, Olivier Gevaert, Guangming Lu

“…The system demonstrated strong performance under data distribution shifts, with AUROC of 0.89 and AUPRC of 0.42 for original strains, and AUROC of 0.77–0.85 and AUPRC of 0.51–0.60 for variants. …”
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Cancer-associated venous thromboembolism and its impact on survival in the ONCOTHROMB12-01 cohort study by Bárbara Lobato-Delgado, Magdalena Ruiz, Carme Font, Vanessa Pachón, Victoria Castellón, Virginia Martínez-Marín, Mercedes Salgado, Eva Martínez, Julia Calzas, Laura Ortega, Ana Rupérez, Oriol Pujol, José Manuel Soria, Andrés Muñoz

“…Moreover, a Cox regression model with stepwise feature selection is trained to identify predictors of prognosis. …”
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Temperature rise of high-speed bearing in gearbox of 5 MW wind turbine based on Bayesian-LightGBM and improved PSO-SVM troubleshooting by Minan Tang, Zhanglong Tao, Jiandong Qiu, Jinping Li, Mingyu Wang, Hongjie Wang, Chuntao Rao

“…Secondly, feature selection is performed on the remaining data using Bayesian-LightGBM to identify 13 key input feature parameters. …”
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Sex differences in loneliness, social isolation, and their impact on psychiatric symptoms and cognitive functioning in schizophrenia by Jinghui Chi, Nannan Liu, Tian Tian, Qiaona Jiang, Chenghao Lu, Yanzhe Li, Xiaofei Zhang, Yanyan Ma, Lili Wang, Shen Li

“…Multiple linear regression models were conducted to test the independent, relative, and synergistic efects of loneliness and social isolation on psychiatric symptoms and cognitive performance for male and female patients separately. …”
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A Study on the Yield Stability of Oilseed Sunflower Genotypes under Drought Stress by Nasrin Akbari, Reza Darvishzadeh

“…On the other hand, in the selection and introduction of varieties, performance, the most important feature of the breeding program, due to its polygenic nature, is strongly affected by biotic and abiotic stresses. …”
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Development of a Nomogram for Prognostic Prediction of Large Hepatocellular Carcinoma With HBV After TACE Combined Conversion Therapy by Xu W, Ding X, Xu Y, Zhang Y, Xu H, Guo L, Li L

“…In the testing cohort (n = 54), two models’ performance was compared with five major staging systems.Results: The preoperative nomogram included alpha–fetoprotein (AFP, HR: 0.486; 95% CI: 0.266– 0.886; P = 0.019) and albumin- bilirubin (ALBI) grade (HR: 0.323; 95% CI: 0.181– 0.578; P < 0.001) and the postoperative nomogram, included AFP (HR: 0.501; 95% CI: 0.271– 0.925; P = 0.027), ALBI grade (HR: 0.356; 95% CI: 0.192– 0.659; P = 0.001), MVI (HR: 0.086; 95% CI: 0.024– 0.192; P < 0.001), and response to TACE combined therapy (HR: 3.367; 95% CI: 1.479– 7.721; P = 0.004). …”
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CONTENT AND STRUCTURE OF SELF-EDUCATIONAL COMPETENCE OF FUTURE BACHELORS IN ECONOMICS: CATEGORICAL AND DEFINITIONAL ANALYSIS by Piven Yaroslav

“…To implement the set tasks, in the study, a number of methods are used; among them a categorical and definitional analysis of scientific research enlightened the essence of self-education and self-educational competence, modelling of components of self-educational competence, specification and systematization of existing theoretical works to determine the structure of self-educational competence of future bachelors in economics. …”
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Innovative engineering training in a competitive educational environment by N. I. Naumkin, N. N. Shekshaeva, E. V. Zabrodina

“…During its developmental process, special attention was paid to the design of models of organisational forms of its implementation, common to which is the high personal motivation of the participants due to the presence of competition, competitive spirit and rivalry. …”
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Network-based machine learning reveals cardiometabolic multimorbidity patterns and modifiable lifestyle factors: a community-focused analysis of NHANES 2015–2018 by Danhui Mao, Junfang Mu, Yajing Li, Lu He, Qianhui Chai, Xin Zhao, Xiaojun Ren, Hui Cheng

“…Among the machine learning algorithms, Logistic Regression exhibited the best performance, with an Accuracy of 0.954 and an AUC-ROC area of 0.998. …”
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Fractal Theory and Its Financial Applications for Improving the Quality of Professional Training at The Higher School of Economics by D. A. Vlasov, P. A. Karasev, A. V. Sinchukov

“…The article presents the didactic potential of modern fractal theory and its financial applications related to modeling and forecasting of financial performance. …”
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Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning by Lucijano Berus, Jernej Hernavs, David Potocnik, Kristijan Sket, Mirko Ficko

“…Different machine learning algorithms, such as Random Forest (RF), k-nearest neighbors (k-NN), and Decision Trees (DT), were used for predictive modeling. Feature extraction was performed using Tsfresh and ROCKET, which allowed us to capture the patterns in the motor current data corresponding to the geometric features of the machined parts. …”
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AgriLiteNet: Lightweight Multi-Scale Tomato Pest and Disease Detection for Agricultural Robots by Chenghan Yang, Baidong Zhao, Madina Mansurova, Tianyan Zhou, Qiyuan Liu, Junwei Bao, Dingkun Zheng

“…This study proposes AgriLiteNet (Lightweight Networks for Agriculture), a lightweight neural network integrating MobileNetV3 for local feature extraction and a streamlined Swin Transformer for global modeling. …”
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White Blood Cell Detection Based on FBDM-YOLOv8s by Borui Sun, Xiangsuo Fan, Jie Meng, Jinfeng Wang, Huajin Chen, Lei Liu

“…Additionally, to attain diversified feature extraction, this article introduces the DBBNCSPELAN4 module, which can perform diversified feature extraction in a multi-branch manner while lightweighting the model, reducing the number of parameters, and speeding up computation. …”
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Optical and SAR Data Fusion Based on Transformer for Rice Identification: A Comparative Analysis from Early to Late Integration by Chenyang He, Jia Song, Huiyao Xu

“…The model exhibits exceptional robustness in cloud-obstructed regions and diverse field patterns, effectively balancing precision (90.98%) and recall (90.35%). …”
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A novel hybrid deep learning approach for super-resolution and objects detection in remote sensing by Muhammad Asif, Mohammad Abrar, Faizan Ullah, Abdu Salam, Farhan Amin, Isabel de la Torre, Mónica Gracia Villar, Helena Garay, Gyu Sang Choi

“…The hybrid model combines Advanced StyleGAN and Swin Transformer. …”
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Pre-Symptomatic Detection of Nicosulfuron Phytotoxicity in Vegetable Soybeans via Hyperspectral Imaging and ResNet-18 by Yun Xiang, Tian Liang, Yuanpeng Bu, Shiqiang Cai, Jingjie Guo, Zhongjing Su, Jinxuan Hu, Chang Cai, Bin Wang, Zhijuan Feng, Guwen Zhang, Na Liu, Yaming Gong

“…Hyperspectral imaging of randomly selected seedling leaves was systematically performed at 1, 3, 5, and 7 days post-treatment. We developed predictive models for herbicide phytotoxicity through advanced machine learning and deep learning frameworks. …”
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Integrating Clinical and Transcriptomic Profiles Associated with Vitamin D to Enhance Disease-Free Survival in Cervical Cancer Recurrence Using the CatBoost Algorithm by Geeitha Senthilkumar, Renuka Pitchaimuthu, Seshathiri Dhanasekaran, Prabu Sankar Panneerselvam

“…Machine learning predictors CatBoost, LightGBM, Extra Trees, and Logistic Regression and feature selection methods such as ANOVA F-test, mutual information, Chi-squared test, and Recursive Feature Elimination (RFE) are used to identify predictors of recurrence, evaluating model performance using accuracy, precision, recall, ROC AUC, confusion matrices, and ROC curves. …”
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GNNMutation: a heterogeneous graph-based framework for cancer detection by Nuriye Özlem Özcan Şimşek, Arzucan Özgür, Fikret Gürgen

“…Conclusions The results indicate that our proposed graph structure and node updating strategy improve cancer classification performance. Additionally, we extended our system with an explainer that identifies a list of causal genes which are effective in the model’s cancer diagnosis predictions. …”
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