Constructing a predictive model for acute mastitis in lactating women based on machine learning by Liujing Zhu, Zuyan Huang, Yan Chen, Guangqiu Li, Liwen Liu

“…By using machine learning (ML) algorithms (Logistic Regression (LR), Naive Bayes (NB), XGBoost, Multilayer Perceptron (MLP)) to train and validate the above data, it aimed to construct a predictive model of the risk factors for the occurrence of acute mastitis in lactating women, and simultaneously analyzed the other influences and effects of these factors on acute mastitis. …”
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Predictive Model of Humidity in Greenhouses through Fuzzy Inference Systems Applying Optimization Methods by Sebastian-Camilo Vanegas-Ayala, Julio Barón-Velandia, Daniel-David Leal-Lara

“…The implementation of a Mamdani-type fuzzy inference system, optimized by a hybrid method combining genetic and interior point algorithms, allowed to predict the relative humidity in greenhouses with high interpretability and precision, with an effectiveness percentage of 90.97% and MSE (mean square error) of 8.2e − 3.…”
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Development and validation of web-based, interpretable predictive models for sepsis and mortality in extensive burns by Shi-Qi Wang, Shi-Qi Wang, Kan Qiu, Qi-Rui Zheng, Bing-Jie Zhou, Ming-Yu Li, Hai-Yan Zhong, Yong Chen, Si-Ming Yuan, Si-Ming Yuan

“…We applied ten machine learning algorithms, including random forest, gradient boosting tree (GBT), and logistic regression, to predict sepsis and mortality. …”
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From predictive analytics to emotional recognition–The evolving landscape of cognitive computing in animal welfare by Suresh Neethirajan

“…The focus is on the strategic application of digital imaging and artificial intelligence to discern subtle behavioral patterns and micro-expressions in livestock, offering a predictive window into their emotional states. The significance of acoustic vocalization analysis in interpreting complex communicative signals and emotional subtleties is highlighted. …”
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Review on Sound-Based Industrial Predictive Maintenance: From Feature Engineering to Deep Learning by Tongzhou Ye, Tianhao Peng, Lidong Yang

“…Sound-based predictive maintenance (PdM) is a critical enabler for ensuring operational continuity and productivity in industrial systems. …”
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Robust predictive framework for diabetes classification using optimized machine learning on imbalanced datasets by Inam Abousaber, Haitham F. Abdallah, Hany El-Ghaish

“…However, class imbalances, where non-diabetic cases dominate, can significantly affect machine learning model performance, leading to biased predictions and reduced generalization.MethodsA novel predictive framework employing cutting-edge machine learning algorithms and advanced imbalance handling techniques was developed. …”
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Deep learning-driven approach for cataract management: towards precise identification and predictive analytics by Shuaixin Lu, Lingling Ba, Jie Wang, Min Zhou, Peiyao Huang, Xiaohua Zhang, Simo Pan, Xinmiao Zhou, Kai Wen, Jing Sun

“…DL could optimize the intraocular lens (IOL) power calculation, predict the risk of complications and long-term surgery requirements. …”
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Development and Evaluation of Neural Network Architectures for Model Predictive Control of Building Thermal Systems by Jevgenijs Telicko, Andris Krumins, Agris Nikitenko

“…To address this challenge, model predictive control based on artificial neural networks can be employed. …”
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Harnessing artificial intelligence for predictive modelling in oral oncology: Opportunities, challenges, and clinical Perspectives by Vishnu Priya Veeraraghavan, Shikhar Daniel, Arun Kumar Dasari, Kaladhar Reddy Aileni, Chaitra patil, Santosh R. Patil

“…Various AI algorithms, including supervised learning, unsupervised learning, and deep learning approaches, have been discussed in the context of oral cancer prediction. …”
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Modeling and computing experiment in the problem of predicting the per capita monetary income of the population based on the methods of correlation and regression analysis by Angelina Vladimirovna Vaskina, Victoria Igorevna Naats

“…The numerical calculations are accompanied by statistical evaluations of predictive performance of the considered mathematical model, performed the analysis and discussion of the results. …”
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Pavement performance model for road maintenance and repair planning: a review of predictive techniques by Krishna Singh Basnet, Jagat Kumar Shrestha, Rabindra Nath Shrestha

“…This paper provides a review of predictive analytics for roads, identifying gaps and limitations in current methodologies. …”
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Corrosion Risk Assessment in Coastal Environments Using Machine Learning-Based Predictive Models by Marta Terrados-Cristos, Marina Diaz-Piloneta, Francisco Ortega-Fernández, Gemma Marta Martinez-Huerta, José Valeriano Alvarez-Cabal

“…Among the models tested, tree-based algorithms, particularly gradient boosting, provided the highest prediction accuracy (F1 score: 0.8673). …”
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Predictive modeling of punchouts in continuously reinforced concrete pavement: a machine learning approach by Ghazi Al-Khateeb, Ali Alnaqbi, Waleed Zeiada

“…In this study, a comprehensive approach that integrates descriptive statistics, correlation analysis, and machine learning algorithms is employed to develop models and predict punchouts in CRCP. …”
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A predictive healthcare model using machine learning and psychological factors for medication adherence by Junwu Dong, Minyi Chu, Yirou Xu

“…This study aims to develop a predictive model for medication adherence behaviour (MAB) employing machine learning techniques, addressing the limitations of traditional correlation-based approaches. …”
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A robust and statistical analyzed predictive model for drug toxicity using machine learning by Deepak Rawat, Rohit Bajaj, Rachit Manchanda, Ankush Mehta, Prabhu Paramasivam, Suraj Kumar Bhagat, Abinet Gosaye Ayanie

“…Abstract Over the years, toxicity prediction has been a challenging task. Artificial intelligence and machine learning provide a platform to study toxicity prediction more accurately with a reduced time span. …”
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Predictive modeling of gestational weight gain: a machine learning multiclass classification study by Audêncio Victor, Hellen Geremias dos Santos, Gabriel Ferreira Santos Silva, Fabiano Barcellos Filho, Alexandre de Fátima Cobre, Liania A. Luzia, Patrícia H.C. Rondó, Alexandre Dias Porto Chiavegatto Filho

“…This study aims to develop and evaluate machine learning models to predict GWG categories: below, within, or above recommended guidelines. …”
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Analyzing Random Forest’s Predictive Capability for Type 1 Diabetes Progression by Niels F. Cleymans, Mark Van De Casteele, Julie Vandewalle, Aster K. Desouter, Frans K. Gorus, Kurt Barbe

“…The second model predicts the transition from multiple AAb+ to the onset of T1D. …”
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Predictive value of dendritic cell-related genes for prognosis and immunotherapy response in lung adenocarcinoma by Zihao Sun, Mengfei Hu, Xiaoning Huang, Minghan Song, Xiujing Chen, Jiaxin Bei, Yiguang Lin, Size Chen

“…Leveraging the Coxboost and random survival forest combination algorithm, we filtered out six DC-related genes on which a prognostic prediction model, DCRGS, was established. …”
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A Predictive Model for Secondary Posttonsillectomy Hemorrhage in Pediatric Patients: An 8‐Year Retrospective Study by Yuting Ge, Wenchuan Chang, Lixiao Xie, Yan Gao, Yue Xu, Huie Zhu

“…Multivariate logistic regression and seven machine learning algorithms were used to construct predictive models. …”
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Stock Price Pattern Prediction Based on Complex Network and Machine Learning by Hongduo Cao, Tiantian Lin, Ying Li, Hanyu Zhang

“…In general, the prediction ability of SVM algorithms is better than that of KNN algorithms.…”
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