Early Diagnosis of Alzheimer’s Disease Using Adaptive Neuro K-Means Clustering Technique by Karan Kumar, Shweta Agrawal, Isha Suwalka, Celestine Iwendi, Cresantus N. Biamba

“…Classification is performed using various algorithms, evaluated on sensitivity, accuracy, precision, and similarity metrics. …”
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Symmetric Grayscale Image Encryption Based on Quantum Operators with Dynamic Matrices by Luis Olvera-Martinez, Manuel Cedillo-Hernandez, Carlos Adolfo Diaz-Rodriguez, Leonardo Faustinos-Morales, Antonio Cedillo-Hernandez, Francisco Javier Garcia-Ugalde

“…Image encryption is crucial for ensuring the confidentiality and integrity of digital images, preventing unauthorized access and alterations. …”
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Developing advanced datadriven framework to predict the bearing capacity of piles on rock by Kennedy C. Onyelowe, Shadi Hanandeh, Viroon Kamchoom, Ahmed M. Ebid, Fabián Danilo Reyes Silva, José Luis Allauca Palta, José Luis Llamuca Llamuca, Siva Avudaiappan

“…This research presents an advanced data-driven framework that integrates multiple machine learning algorithms to predict the bearing capacity of piles based on geotechnical and in-situ test parameters. …”
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Predicting rapid kidney function decline in middle-aged and elderly Chinese adults using machine learning techniques by Yang Li, Kun Zou, Yixuan Wang, Yucheng Zhang, Jingtao Zhong, Wu Zhou, Fang Tang, Lu Peng, Xusheng Liu, Lili Deng

“…Furthermore, the study integrated SHapley Additive exPlanations (SHAP) to boost the interpretability of the model. …”
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Preventing Health Risks Through Intelligent Medical Appointment Management Using Disease and Attendance Propensity by Fredy Troncoso-Espinosa, Guillermo Latorre-Nunez, Catalina Valenzuela-Nunez, Juan San Martin-Duran

“…Subsequently, machine learning algorithms are applied to patient historical data to obtain more precise and realistic estimates of these propensities, which are then integrated into the model to adjust appointment allocation according to each patient’s individual risk. …”
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CT-based radiomics deep learning signatures for non-invasive prediction of metastatic potential in pheochromocytoma and paraganglioma: a multicohort study by Yongjie Zhou, Yuan Zhan, Jinhong Zhao, Linhua Zhong, Fei Zou, Xuechao Zhu, Qiao Zeng, Jiayu Nan, Lianggeng Gong, Yongming Tan, Lan Liu

“…Results The support vector machine radiomics and 2D ResNet-50 models demonstrated good performance. By integrating these two models with intratumoral necrosis features, we constructed a combined model that achieved high accuracy, with area under the curve (AUC) values of 0.90 for the training, 0.86 for the test1, and 0.88 for the test2 sets. …”
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Enhancing Transpiration Estimates: A Novel Approach Using SIF Partitioning and the TL-LUE Model by Tewekel Melese Gemechu, Baozhang Chen, Huifang Zhang, Junjun Fang, Adil Dilawar

“…Existing methodologies, including traditional techniques like the Penman–Monteith model, remote sensing approaches utilizing Solar-Induced Fluorescence (SIF), and machine learning algorithms, have demonstrated varying levels of effectiveness in ET estimation. …”
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Optimization of multi-objective feature regression models for designing performance assessment methods in college and university educational reform by Fengjun Qi, Zhenping Liu, Wenzheng Zhang, Zhenjie Sun

“…Experimental evaluations on three datasets—Education Reform (EDU-REFORM), Programme for International Student Assessment (PISA), and National Assessment of Educational Progress (NAEP)—demonstrate the superior performance of MOFR-LSF, achieving relative root mean square error (RRMSE) values of 0.634, 0.332, and 0.925, respectively, outperforming existing multi-objective regression algorithms. …”
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A Machine Vision Method for Detecting Pineapple Fruit Mechanical Damage by Jiahao Li, Baofeng Mai, Tianhu Liu, Zicheng Liu, Zhaozheng Liang, Shuyang Liu

“…Finally, a calibration object with a known surface area is used to derive both the depth values and pixel area. By integrating the depth information with the pixel area of the binary image, the damaged area of the pineapple is calculated. …”
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Complex q-Rung Orthopair Fuzzy N-Soft Sets: A New Model with Applications by Muhammad Akram, Faiza Wasim, Ahmad N. Al-Kenani

“…Moreover, we establish two competent multicriteria decision-making algorithms that capture the nuances of periodical inconsistent data. …”
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Neural Personalized Ranking via Poisson Factor Model for Item Recommendation by Yonghong Yu, Li Zhang, Can Wang, Rong Gao, Weibin Zhao, Jing Jiang

“…The proposed method integrates the ranking-based poisson factor model into the neural networks. …”
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Decision vector model in predicting social behavior (on the example of the secondary analysis of the pre-election surveys) by N. S. Babich, S. M. Kharun

“…The article considers a decision vector model that can be used to approximate actual behavior with some formal rules that allow to construct algorithms for predicting future states. The authors tested the reliability of ex post facto predictions on the example of the unsuccessfully predicted 2013 Moscow mayoral elections. …”
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Artificial Intelligence Technologies in Criminal Procedural Proving by M. S. Spiridonov

“…A conclusion is substantiated that the assessment of evidences with mathematical algorithms, in which preset values of each evidence quality are used, contradict to the principle of free assessment of evidences in the criminal procedure. …”
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Identification of Fake Comments in E-Commerce Based on Triplet Convolutional Twin Network and CatBoost Model by Juanjuan Peng

“…Compared with the other two comparison algorithms, the detection time required by the proposed model was the shortest at 115us and consumed the least amount of resources. …”
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Net buffer load during regional citrate anticoagulated continuous renal replacement therapy. by Innas Forsal, Dominique Pouchoulin, Viktoria Roos, Jorge Echeverri, Marcus Ewert Broman

“…<h4>Methods</h4>Algorithms for estimating the net buffer load were developed. …”
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Enhancing Machine Learning Models Through PCA, SMOTE-ENN, and Stochastic Weighted Averaging by Youngjin Han, Inwhee Joe

“…An ensemble model combining seven machine learning algorithms—Logistic Regression, Support Vector Machine, KNN, Random Forest, XGBoost, LightGBM, and CatBoost—was applied to predict survival outcomes. …”
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The application of super-resolution ultrasound radiomics models in predicting the failure of conservative treatment for ectopic pregnancy by Mingyan Zhang, Junfa Sheng

“…Feature selection involved statistical testing and Least Absolute Shrinkage and Selection Operator (LASSO) regression. Random forest algorithms were used to construct NR and SR models. …”
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Heat transfer with magnetic force and slip velocity on non-Newtonian fluid flow through a porous medium by Muhammad Ramzan, Muhammad Shahryar, Shajar Abbas, Muhammad Amir, Shaxnoza Ravshanbekovna Saydaxmetova, Rashid Jan, Afnan Al Agha, Hakim AL Garalleh

“…Model validation is achieved by comparing results obtained through algorithmic solutions, confirming the robustness of the fractional approach by taking the values of fractional parameter γ in the range 0.2≤γ≤1, whereas the values of slip parameter λ lies in the range 0≤λ≤0.8. …”
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Validation of Self-reported Medical Condition in the Taiwan Biobank by Chi-Shin Wu, Le-Yin Hsu, Chen-Yang Shen, Wei J. Chen, Shi-Heng Wang

“…These findings underscore the need for further investigation, especially when these variables are crucial to research objectives. Integrating complementary databases, such as clinical diagnoses, prescription records, and medical procedures, can enhance accuracy through customized algorithms based on disease categories and participant characteristics and optimize sensitivity or positive predictive values to align with specific research objectives.…”
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Detecting Changes in Soil Fertility Properties Using Multispectral UAV Images and Machine Learning in Central Peru by Lucia Enriquez, Kevin Ortega, Dennis Ccopi, Claudia Rios, Julio Urquizo, Solanch Patricio, Lidiana Alejandro, Manuel Oliva-Cruz, Elgar Barboza, Samuel Pizarro

“…The RF model outperformed others, with R² values of 72% for N, 83% for P, 87% for K, 85% for OM, and 70% for EC in 2023. …”
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