Improving machine learning algorithm for risk of early pressure injury prediction in admission patients using probability feature aggregation by Shu-Chen Chang, Shu-Mei Lai, Mei-Wen Wu, Shou-Chuan Sun, Mei-Chu Chen, Chiao-Min Chen

“…Objective Pressure injuries (PIs) pose a significant concern in hospital care, necessitating early and accurate prediction to mitigate adverse outcomes. Methods The proposed approach receives multiple patients records, selects key features of discrete numerical based on their relevance to PIs, and trains a random forest (RF) machine learning (ML) algorithm to build a predictive model. …”
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An efficient method for predicting temperature field of PC beams with CSWs using thermocouple numerical analysis and random forest algorithm by Haiping Zhang, Hao Long, Fanghuai Chen, Yuan Luo, Xinhui Xiao, Yang Deng, Naiwei Lu, Yang Liu

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Vortex-Induced Vibration Performance Prediction of Double-Deck Steel Truss Bridge Based on Improved Machine Learning Algorithm by Yang Yang, Huiwen Hou, Gang Yao, Bo Wu

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Modeling and Numerical Prediction on Mechanical Behaviors of Hybrid Fiber Reinforced Polymer Bio Composites Using Fuzzy Logic Algorithm by Vinoth Viswanathan, Sathiyamurthy Subbarayan, Ananthi Narayanaswamy, Devi Panneerselvam, Prabhakaran Jayasankar

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Prediction of Earthquake Death Toll Based on Principal Component Analysis, Improved Whale Optimization Algorithm, and Extreme Gradient Boosting by Chenhui Wang, Xiaotao Zhang, Xiaoshan Wang, Guoping Chang

“…To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). …”
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Machine Learning for the Prediction of Acute Kidney Injury in Critically Ill Patients With Coronary Heart Disease: Algorithm Development and Validation by Yike Li, Mingyang Xiao, Yaqian Li, Lulu Lv, Shanshan Zhang, Yuhui Liu, Juan Zhang

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A Genetic algorithm aided hyper parameter optimization based ensemble model for respiratory disease prediction with Explainable AI by Balraj Preet Kaur, Harpreet Singh, Rahul Hans, Sanjeev Kumar Sharma, Chetna Sharma, Md. Mehedi Hassan

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Prediction of chloride concentration in concrete under multi-salt environment: Optimization of integrated algorithm based on MSCPO and interpretability analysis by Daming Luo, Kanglei Du, Ditao Niu

Subjects: “…Metaheuristic optimization algorithm…”
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NGBoost algorithm-based prediction of mechanical properties of a hot-rolled strip and its interpretability research with ANOVA values by Hongyi Wu, Jinwen Jin, Zhiwei Li

“…The study focused on predicting tensile strength, yield strength, and elongation of hot-rolled strip steel and compared the predictive results with those obtained from the gradient boosting algorithm, Lasso regression, and decision tree algorithms. …”
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Study on risk factors of impaired fasting glucose and development of a prediction model based on Extreme Gradient Boosting algorithm by Qiyuan Cui, Jianhong Pu, Wei Li, Yun Zheng, Jiaxi Lin, Lu Liu, Peng Xue, Jinzhou Zhu, Mingqing He

“…ObjectiveThe aim of this study was to develop and validate a machine learning-based model to predict the development of impaired fasting glucose (IFG) in middle-aged and older elderly people over a 5-year period using data from a cohort study.MethodsThis study was a retrospective cohort study. …”
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Predicting the Cetane Number of Biodiesel using two AI-Models: the Gradient-based ANN and ANN Optimized by Genetic Algorithm by Hadis Tanha, Fatemeh Bashipour

“…They were the gradient-based artificial neural network (GB-ANN) and the multi-layer-perceptron ANN optimized by the genetic algorithm (GA-ANN) for the first time. The three input variablesof the model for predicting the target variable of the biodiesel CN are the average number of carbon atoms, average number of double bonds, and average molecular weight of the fatty acid methyl esters. …”
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Novel machine learning algorithm in risk prediction model for pan-cancer risk: application in a large prospective cohort by Chi-Pang Wen, Xifeng Wu, Qingfeng Hu, Huakang Tu, Shan Pou Tsai, David Ta-Wei Chu

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Application of Decision Tree (M5Tree) Algorithm for Multicrop Yield Prediction of the Semi-Arid Region of Maharashtra, India by Kalpesh Borse, Prasit Agnihotri

“…Modern artificial intelligence algorithms have shown to be highly useful tools for accurately predicting agricultural production. …”
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Enhanced CO₂ Emissions Prediction Using Temporal Fusion Transformer Optimized by Football Optimization Algorithm by Amel Ali Alhussan, Marwa Metwally

Subjects: “…carbon dioxide emissions prediction…”
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WCN24-657 ARTIFICIAL INTELLIGENCE IN PREDICTING PROGRESSION IN ADVANCED CKD: FROM ALGORITHM DEVELOPMENT TO REAL-WORLD DEPLOYMENT by Ricardo Aguilar Grajeda, Priyanka Arya, Chin-Chi Kuo, Mandar Gori, Suresha Venkataraya, Joel Fernandes, Sanjay Singh, Yu-Ting Lin, Hsiu-Yin Chiang, Yi-Chun Chan, Min-Yen Wu, Zi-Han Lin, Arsh Kumar Jain

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A Genetic algorithm aided hyper parameter optimization based ensemble model for respiratory disease prediction with Explainable AI. by Balraj Preet Kaur, Harpreet Singh, Rahul Hans, Sanjeev Kumar Sharma, Chetna Sharma, Md Mehedi Hassan

“…Moreover, among all the hyperparameter-optimized algorithms, adaboost algorithm outperformed all the other hyperparameter-optimized algorithms. …”
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Efficient Recovery of Linear Predicted Coefficients Based on Adaptive Steepest Descent Algorithm in Signal Compression for End-to-End Communications by Abel Kamagara, Abbas Kagudde, Baris Atakan

“…Herein, the steepest descent algorithm is applied at the receiver to decode the affected linear predicted coefficients. …”
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Prediction of the Punching Load Strength of SCS Slabs with Stud-Bolt Shear Connectors Using Numerical Modeling and GEP Algorithm by Mehdi Yousefi, Mohammad Golmohammadi, Seyed Hashem Khatibi, Majid Yaghoobi

“…Finally, using the experimental setup and gene expression programming (GEP) algorithm, several numerical models were planned to predict the maximum strength of the slabs and a simple relation was proposed. …”
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An ideally designed deep trust network model for heart disease prediction based on seagull optimization and Ruzzo Tompa algorithm by Yuan Jin, Yunliang Lai, Azadeh Noori Hoshyar, Nisreen Innab, Meshal Shutaywi, Wejdan Deebani, A. Swathi

“…Although recent studies propose comprehensive automated diagnostic systems, these systems tend to focus on one aspect, such as feature selection, prioritization, or predictive accuracy. A more complete approach that considers all of these factors can improve the efficiency of a cardiac prediction system. …”
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Comparison of Support Vector Machine and Decision Tree Algorithm Performance with Undersampling Approach in Predicting Heart Disease Based on Lifestyle by Gusti Ayu Putu Febriyanti, Anna Baita

“…This study evaluates the performance of two machine learning algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT), in predicting heart disease risk by applying undersampling techniques to handle data imbalance. …”
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