Development of machine learning models to predict the risk of fungal infection following flexible ureteroscopy lithotripsy by Haofang Zhang, Changbao Xu, Chenge Hu, Yunlai Xue, Daoke Yao, Yifan Hu, Ankang Wu, Miao Dai, Hang Ye

“…Use LASSO regression to screen clinical features based on the training set. Nine machine learning algorithms, Logistic Regression (LR), k-Nearest Neighbours (KNN), Support Vector Machines (SVM), Random Forest (RF), Categorical Boosting (CatBoost), eXtreme Gradient Boosting (XGBoost), Adaptive Boosting (AdaBoost), Gradient Boosting Machines (GBM), and Neural Network (NNet), were used to construct models. …”
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Product perceptual design optimization model based on BP neural network by Lei Yong

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Development and validation of a probability-assessment nomogram for non-suicidal self-injury in hospitalized adolescents and young adults with mental disorders by Qi Liu, Yanjuan Ren, Yalin Huang, Ruyi Xie, Yinyuan Li, Zaiquan Dong, Xiaoxia Zhang

“…Model performance was evaluated based on discrimination, calibration, and decision curve analysis (DCA). …”
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Operational strategies to the mechanical performance assessment of concrete with the neural network and artificial intelligence by Hadi Faghihmaleki, Mehdi Ghadiri

“…In this research, the data used were first normalized and then the desired data were trained using the Lorenberg Marquardt algorithm.Findings: The evaluation criteria of artificial neural network models were obtained using evaluation and error and the results showed that the use of 10 hidden layers had the highest correlation coefficient and the lowest error. …”
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Computational intelligence analysis on drug solubility using thermodynamics and interaction mechanism via models comparison and validation by Ahmad J. Obaidullah, Wael A. Mahdi

“…Also, Fireworks Algorithm (FWA) is employed for hyper-parameter tuning in this work. …”
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Comparative Study of SVM, KNN, and Naïve Bayes for Sentiment Analysis of Religious Application Reviews by Heti Aprilianti, Khothibul Umam, Maya Rini Handayani

“…This study aims to evaluate and compare the performance of three machine learning algorithms—Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), and Naïve Bayes—for sentiment classification of user reviews on the NU Online application in the Google Play Store. …”
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Prediction of Liquefaction-Induced Lateral Displacements Using Hybrid GBRT and EOA by Arash Ziaie, Bahareh Mehdizadeh, Farzad Safi Jahanshahi, Nazanin Ahmadi, Ali Reza Ghanizadeh

“…Consequently, predicting these lateral movements is vital for evaluating the effects of earthquakes on buildings and infrastructures in regions susceptible to liquefaction. …”
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An extension of the Spiegelhalter-Knill-Jones method for continuous covariates in clinical decision making by Bart K. M. Jacobs, Tafadzwa Maseko, Lutgarde Lynen, Aquiles Rodrigo Henriquez-Trujillo, Jozefien Buyze

“…Abstract Background There is still demand for algorithms that can be used at the point of care, especially when dealing with events that do not present with a single obvious clinical indicator. …”
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Explainable Predictive Factors for Inter-Agency Partnership Success by Nicola Drago, Goncalo Afonso Braz, Tullio Vardanega

“…By applying Shapley’s additive explanation values to trained models, we ranked factors by criticality, identifying their Top-10 rank. …”
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A multicenter study on developing a prognostic model for severe fever with thrombocytopenia syndrome using machine learning by Jian-She Xu, Kai Yang, Bin Quan, Jing Xie, Yi-Shan Zheng, Yi-Shan Zheng

“…The clinical utility of the best-performing model was evaluated through decision curve analysis (DCA) based on net benefit. …”
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Transport Capacity Maximization in Rail Mass Transit Stations Under Uncertainty by Adrian Fernandez-Rodriguez, Maria Dominguez, Asuncion P. Cucala, Antonio Fernandez-Cardador

“…At the upper level, a genetic algorithm determines the optimal sequence of train services and platform assignments. …”
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A strategy for out-of-roundness damage wheels identification in railway vehicles based on sparse autoencoders by Jorge Magalhães, Tomás Jorge, Rúben Silva, António Guedes, Diogo Ribeiro, Andreia Meixedo, Araliya Mosleh, Cecília Vale, Pedro Montenegro, Alexandre Cury

“…This automatic damage identification algorithm is based on the vertical acceleration evaluated on the rails using a virtual wayside monitoring system and involves the application of a two-step procedure. …”
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Embedding Moving Baseline RTK for High-Precision Spatiotemporal Synchronization in Virtual Coupling Applications by Susu Huang, Baigen Cai, Debiao Lu, Yang Zhao, Miao Zhang, Linyu Shang

“…The proposed framework was evaluated through comprehensive simulations and field experiments. …”
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Early Detection of Alzheimer’s Disease via Machine Learning-Based Microwave Sensing: An Experimental Validation by Leonardo Cardinali, Valeria Mariano, David O. Rodriguez-Duarte, Jorge A. Tobón Vasquez, Rosa Scapaticci, Lorenzo Crocco, Francesca Vipiana

“…Data classification consists of two steps: binary classification to identify the disease presence and multi-class classification to evaluate its stage. The algorithm is trained and validated through controlled experiments mimicking various pathological severities with an anthropomorphic multi-tissue head phantom. …”
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Deep Learning for Weed Detection and Segmentation in Agricultural Crops Using Images Captured by an Unmanned Aerial Vehicle by Josef Augusto Oberdan Souza Silva, Vilson Soares de Siqueira, Marcio Mesquita, Luís Sérgio Rodrigues Vale, Thiago do Nascimento Borges Marques, Jhon Lennon Bezerra da Silva, Marcos Vinícius da Silva, Lorena Nunes Lacerda, José Francisco de Oliveira-Júnior, João Luís Mendes Pedroso de Lima, Henrique Fonseca Elias de Oliveira

“…Evaluation metrics were used, which included training efficiency (mAP50 and mAP50-90), precision, accuracy, and recall in the model’s evaluation and comparison. …”
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The study of thermodynamic mechanisms of advection-cooled sea fogs for two cases based on the WRF model by Xin-Ya Ye, Fei-Fei Shen, Fei-Fei Shen, Fei-Fei Shen, Hai-Yan Fei, Qi-Long Sun, Ai-Qing Shu, Shen Wan, He Chen

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An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets by Ahmad Salehiyan, Pardis Sadatian Moghaddam, Masoud Kaveh

“…In this study, we propose an optimized hybrid DL framework that combines a transformer, generative adversarial network (GAN), and autoencoder (AE) components, referred to as Transformer–GAN–AE, for robust intrusion detection in Edge and IIoT environments. To enhance the training and convergence of the GAN component, we integrate an improved chimp optimization algorithm (IChOA) for hyperparameter tuning and feature refinement. …”
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Physics-Informed Deep Neural Network for Low Sidelobe Time-Modulated Antenna Array Synthesis With Harmonic Suppression by Tarek Sallam, Qun Wang, Ahmed M. Attiya

“…Additionally, the approach is compared to genetic algorithm (GA) which corresponds to a representative evolutionary optimization algorithm. …”
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An Assist-as-Needed Control Strategy Based on a Subjective Intention Decline Model by Hao Yan, Fangcao Zhang, Xingao Li, Chenchen Zhang, Yunjia Zhang, Yongfei Feng

“…The limb movement assessment module collects information such as interaction force and position error during training and proposes a method for evaluating the motion state of the affected limb. …”
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Enhancing Education with Machine Learning: Predicting Student Readability Scores by Claire Bell

“…The research leverages a dataset of 1,000 English texts to evaluate and compare the performance of RFC, the Sooty Tern Optimization Algorithm (STOA), and the Gold Rush Optimizer (GRO) in predicting readability ratings. …”
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