Optimal design of agro-residue filled poly(lactic acid) biocomposites using an integrated CRITIC-CoCoSo multi-criteria decision-making approach by László Lendvai, Sándor Kálmán Jakab, Tej Singh

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Coffee Leaf Rust Disease Detection and Implementation of an Edge Device for Pruning Infected Leaves via Deep Learning Algorithms by Raka Thoriq Araaf, Arkar Minn, Tofael Ahamed

“…All labeled images were used to train the YOLOv5 and YOLOv8 algorithms through the convolutional neural network (CNN). …”
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Predictive modeling of arginine vasopressin deficiency after transsphenoidal pituitary adenoma resection by using multiple machine learning algorithms by Yuyang Chen, Jiansheng Zhong, Haixiang Li, Kunzhe Lin, Liangfeng Wei, Shousen Wang

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Integrated neural network and evolutionary algorithm approach for liver fibrosis staging: Can artificial intelligence reduce patient costs? by Ali Nazarizadeh, Touraj Banirostam, Taraneh Biglari, Mohammadreza Kalantarhormozi, Fatemeh Chichagi, Amir H Behnoush, Mohammad A Habibi, Ramin Shahidi

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Construction of risk prediction model of sentinel lymph node metastasis in breast cancer patients based on machine learning algorithm by Qianmei Yang, Cuifang Liu, Yongyue Wang, Guifang Dong, Jinghuan Sun

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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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Experience with artificial intelligence algorithms for the diagnosis of vertebral compression fractures based on computed tomography: from testing to practical evaluation by Zlata R. Artyukova, Alexey V. Petraikin, Nikita D. Kudryavtsev, Fedor A. Petryaykin, Dmitry S. Semenov, Daria E. Sharova, Zhanna E. Belaya, Anton V. Vladzimirskyy, Yuriy A. Vasilev

“…CONCLUSION: Artificial intelligence algorithms for the automatic diagnosis of vertebral compression fractures have been tested, demonstrating the high quality of their operation. artificial intelligence algorithms can be applied as a supplementary tool in the medical decision support system.…”
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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

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Optimizing Curriculum Vitae Concordance: A Comparative Examination of Classical Machine Learning Algorithms and Large Language Model Architectures by Mohammed Maree, Wala’a Shehada

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Supervised machine learning algorithms for the classification of obesity levels using anthropometric indices derived from bioelectrical impedance analysis by Rodrigo Yáñez-Sepúlveda, Aldo Vásquez-Bonilla, Rodrigo Olivares, Pablo Olivares, Juan Pablo Zavala-Crichton, Claudio Hinojosa-Torres, Catalina Muñoz-Strale, Frano Giakoni-Ramírez, Josivaldo de Souza-Lima, Jacqueline Páez-Herrera, Jorge Olivares-Arancibia, Tomás Reyes-Amigo, Guillermo Cortés-Roco, Juan Hurtado-Almonacid, Eduardo Guzmán-Muñoz, Nicole Aguilera-Martínez, José Francisco López-Gil, Boryi A. Becerra-Patiño, Juan David Paucar-Uribe, Exal Garcia-Carrillo, Vicente Javier Clemente-Suárez

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Prediction of Crop Yield by Support Vector Machine Coupled with Deep Learning Algorithm Procedures in Lower Kulfo Watershed of Ethiopia by Abebe Temesgen Ayalew, Tarun Kumar Lohani

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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

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Enhancing sentiment analysis in tourism reviews: A comparative study of algorithms in ASPECT-BASED SENTIMENT ANALYSIS and EMOTION DETECTION by Viktor Handrianus Pranatawijaya, Putu Bagus Adidyana Anugrah Putra, Ressa Priskila, Novera Kristianti

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Determining the parameters of different Muskingum models with chimp optimization algorithm and verifying them using the Daechung flood of 2014 and 2018 by Farshad Haiati, Behrouz Yaghoubi, Sara Nazif

“…The chimp meta-heuristic algorithm has been used to determine the parameters of different Muskingum models, which are defined as optimization problems. …”
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Investigation of Artificial Intelligence Techniques for the Management of Cataract Disease: A Systematic Review by Zahra Karbasi, Michaeel Motaghi Niko, Maryam Zahmatkeshan

“…The results indicated that convolutional neural network algorithms (6 articles), recurrent neural networks (1 article), deep convolutional networks (1 article), support vector machines (2 articles), transfer learning (1 article), decision trees (4 articles), random forests (4 articles), logistic regression (3 articles), Bayesian algorithms (3 articles), XGBoost (3 articles), and K-nearest neighbors clustering algorithms (2 articles) were the artificial neural network and machine learning techniques and algorithms utilized. …”
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Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-parametric Tests by Milena Gajić, Sanela Arsić, Jordan Radosavljević, Miroljub Jevtić, Bojan Perović, Dardan Klimenta, Miloš Milovanović

“…The proposed procedure contains the following: (i) the behavior analysis of the algorithms when solving the CEED problem, using non-parametric tests, and (ii) the ranking of the algorithms using the PROMETHEE/GAIA multi-criteria decision-making method. …”
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Comparison of Machine-Learning Algorithms for Near-Surface Air-Temperature Estimation from FY-4A AGRI Data by Ke Zhou, Hailei Liu, Xiaobo Deng, Hao Wang, Shenglan Zhang

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An enhanced fruit fly optimization algorithm with random spare and double adaptive weight strategies for oil and gas production optimization by Xu Wang, Jingfu Shan

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A Real-Time High-Resolution Multi-Focus Image Fusion Algorithm Based on Multi-Scale Feature Aggregation by Huawei Chen, Xingkai Du, Hongchuan Huang, Tingyu Zhao

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SAER : Comparison of Rule Prediction Algorithms on Constructing a Corpus for Taxation Related Tweet Aspect-Based Sentiment Analysis by Annisa Mufidah Sopian, Ridwan Ilyas, Fatan Kasyidi, Asep Id Hadiana

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