Exploring non-invasive biomarkers for pulmonary nodule detection based on salivary microbiomics and machine learning algorithms by Chunxia Huang, Qiong Ma, Xiao Zeng, Jiawei He, Fengming You, Xi Fu, Yifeng Ren

“…Furthermore, the Bayesian optimization algorithm was used to optimize this best-performing model. …”
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Advances in the Application of Intelligent Algorithms to the Optimization and Control of Hydrodynamic Noise: Improve Energy Efficiency and System Optimization by Maosen Xu, Bokai Fan, Renyong Lin, Rong Lin, Xian Wu, Shuihua Zheng, Yunqing Gu, Jiegang Mou

“…To this end, this paper systematically reviews progress in the application of intelligent algorithms in hydrodynamic noise research, focusing on their advantages in the optimal design of noise sources, noise prediction, and control strategy optimization. …”
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Application of Imaging Algorithms for Gas–Water Two-Phase Array Fiber Holdup Meters in Horizontal Wells by Ao Li, Haimin Guo, Yue Niu, Xin Lu, Yiran Zhang, Haoxun Liang, Yongtuo Sun, Yuqing Guo, Dudu Wang

“…In horizontal wellbores, precisely predicting flow patterns using conventional approaches is often problematic. …”
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Comparison of principal component analysis algorithms for imputation in agrometeorological data in high dimension and reduced sample size. by Valter Cesar de Souza, Sergio Augusto Rodrigues, Luís Roberto Almeida Gabriel Filho

“…Based on statistical evaluation, the NIPALS-PCA, EM-PCA, and IM imputation models proved suitable for estimating missing ETo data, with PCA imputation models in the NIPALS and EM algorithms showing the most promise. Future research should explore the effectiveness of various imputation methods in diverse climatic and geographical contexts, as well as develop new techniques considering the temporal and spatial structure of meteorological data, to advance understanding and climate prediction.…”
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Digital Transformation in Aftersales and Warranty Management: A Review of Advanced Technologies in I4.0 by Vicente González-Prida, Carlos Parra Márquez, Pablo Viveros Gunckel, Fredy Kristjanpoller Rodríguez, Adolfo Crespo Márquez

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Smart Microgrid Management and Optimization: A Systematic Review Towards the Proposal of Smart Management Models by Paul Arévalo, Dario Benavides, Danny Ochoa-Correa, Alberto Ríos, David Torres, Carlos W. Villanueva-Machado

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Clinical Algorithms and the Legacy of Race-Based Correction: Historical Errors, Contemporary Revisions and Equity-Oriented Methodologies for Epidemiologists by Horsfall LJ, Bondaronek P, Ive J, Poduval S

“…Laura J Horsfall, Paulina Bondaronek, Julia Ive, Shoba Poduval Institute of Health Informatics, University College London, London, UKCorrespondence: Laura J Horsfall, Email laura.horsfall@ucl.ac.ukAbstract: Clinical algorithms are widely used tools for predicting, diagnosing, and managing diseases. …”
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Detection and Classification of Emotional State Based on Speech Signal by Hiba Younis, Mrewan Mustafa, Rahma Raad

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Prediction of Influence of Environmental Factors on the Toxicity of Pentachlorophenol on <i>E. coli</i>-Based Bioassays by Sulivan Jouanneau, Gerald Thouand

“…This study addresses this challenge by aiming to develop an algorithm capable of predicting the effect of environmental conditions on the impact of a toxicant, pentachlorophenol (PCP). …”
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Correction of Disturbances Influence on Results of Elongated Objects's Probe Microscopy Using Predictive Relief Estimates by P. V. Gulyaev

“…The peculiarity of predictive images is the sharpening of areas distorted by disturbances. …”
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A Study on the Application of Explainable AI on Ensemble Models for Predictive Analysis of Chronic Kidney Disease by K. M. Tawsik Jawad, Anusha Verma, Fathi Amsaad, Lamia Ashraf

“…The goal of this research is to first develop an accurate ensemble model for prediction of unseen cases of CKD given the biomarkers. …”
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Predictive direct control strategy of unified power quality conditioner based on power angle control by Guifeng Wang, Zewen Wu, Zhan Liu

“…This approach simplifies the controller structure and alleviates the control algorithm’s complexity. Based on a detailed analysis of the PAC mechanism, an instantaneous power angle determination method is proposed based on the reactive power equalization technique, and a predictive direct control strategy given the current generation mechanism is constructed for the series and shunt sides of the UPQC, considering the active power balance of the UPQC system and the principle of constant load fundamental voltage amplitude. …”
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Predicting the Tensile Strength of Plant Leaves Based on GA-SVM by Wei Chang, Meihong Liu, Yayu Huang, Junjie Lei, Kai Wu

“…A comparative analysis with other predictive algorithms demonstrates that the GA-SVM model achieves the lowest prediction error and highest accuracy, with mean absolute error and root mean squared error values of 0.0774 and 0.0745, respectively. …”
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Machine Learning and Multilayer Perceptron-Based Customized Predictive Models for Individual Processes in Food Factories by Byunghyun Lim, Dongju Kim, Woojin Cho, Jae-Hoi Gu

“…Additionally, it proposes a customized predictive model employing four machine learning algorithms—linear regression, decision tree, random forest, and k-nearest neighbor—as well as two deep learning algorithms: long short-term memory and multi-layer perceptron. …”
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Prediction of Airline Ticket Price Using Machine Learning Method by Hüseyin Korkmaz

“…This paper aims to predict ticket prices based on airline flight data using ML algorithms and to compare the performance of ML algorithms. …”
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Optimized solar PV integration for voltage enhancement and loss reduction in the Kombolcha distribution system using hybrid grey wolf-particle swarm optimization by Awot Getachew Abera, Tefera Terefe Yetayew, Assen Beshr Alyu

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Sizing and Characterization of Load Curves of Distribution Transformers Using Clustering and Predictive Machine Learning Models by Pedro Torres-Bermeo, Kevin López-Eugenio, Carolina Del-Valle-Soto, Guillermo Palacios-Navarro, José Varela-Aldás

“…The results show that DTW with K-means provides the best segmentation, with a cross-correlation similarity of 0.9552 and a temporal consistency index of 0.9642. For predictive modeling, supervised algorithms were tested, where Random Forest achieved the highest accuracy in predicting the corresponding load curve type for each transformer (0.78), and the SVR model provided the best performance in predicting the maximum load, explaining 90% of the load variability (R² = 0.90). …”
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A predictive analytics approach with Bayesian-optimized gentle boosting ensemble models for diabetes diagnosis by Behnaz Motamedi, Balázs Villányi

“…Nevertheless, enhancing boosting algorithms to achieve superior predictive accuracy continues to be a difficult task. …”
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The urban heat Island effect: A review on predictive approaches using artificial intelligence models by Ali Najah Ahmed, Nouar AlDahoul, Nurhanani A. Aziz, Y.F. Huang, Mohsen Sherif, Ahmed El-Shafie

“…While conventional ML algorithms remain widely used, DL and hybrid models have shown superior performance in predictive accuracy. …”
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Machine learning predictive performance in road accident severity: A case study from Thailand by Ittirit Mohamad, Sajjakaj JomnonKwao, Vatanavongs Ratanavaraha

“…This study evaluates the predictive performance of multiple supervised machine learning algorithms in classifying accident severity, addressing the gap in prior research that lacks a comparative analysis of multiple models trained on large-scale crash data. …”
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