Practical Recommendations for Artificial Intelligence and Machine Learning in Antimicrobial Stewardship for Africa by Tafadzwa Dzinamarira, Elliot Mbunge, Claire Steiner, Enos Moyo, Adewale Akinjeji, Kaunda Yamba, Loveday Mwila, Claude Mambo Muvunyi

“…The deployment of AI‐driven solutions presents unprecedented opportunities for optimizing treatment regimens, predicting resistance patterns, and improving clinical workflows. …”
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GuardianML: Anatomy of Privacy-Preserving Machine Learning Techniques and Frameworks by Nges Brian Njungle, Eric Jahns, Zhenqi Wu, Luigi Mastromauro, Milan Stojkov, Michel A. Kinsy

“…Privacy-preserving machine learning PPML aims to safeguard the confidentiality of both data and models and ensure that sensitive information remains protected during training and inference processes. …”
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Robust dispatch for electrical–thermal combined smart building considering impacts of uncertainties on thermal side by Weijie He, Fanrong Wei, Xiangning Lin, Samir M. Dawoud

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The Whale Optimization Algorithm and Markov Chain Monte Carlo-Based Approach for Optimizing Teacher Professional Development in Creative Learning Design with Technology by Kalliopi Rigopouli, Dimitrios Kotsifakos, Yannis Psaromiligkos

“…In this article, we show that metaheuristic algorithms like the whale optimization algorithm, validated by a Markov chain technique like Markov Chain Monte Carlo, can help not only in areas like machine learning but also in fields without structured data, like creativity in technology-enhanced learning design. …”
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Interpretation of chemical reaction yields with graph neural additive network by Youngchun Kwon, Yongsik Jung, Youn-Suk Choi, Seokho Kang

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Use of CatBoost algorithm to identify the need for surgery in infants with necrotizing enterocolitis by Xinyun Jin, Xinyun Jin, Wenqiang Sun, Wenqiang Sun, Yihui Li, Yihui Li, Yinglin Su, Lingqi Xu, Lingqi Xu, Xueping Zhu

“…Feature importance was ranked using the SHapley Additive exPlanation method and model optimization was performed using feature culling. …”
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Confusion Matrices: A Unified Theory by Johan Erbani, Pierre-Edouard Portier, Elod Egyed-Zsigmond, Diana Nurbakova

“…The confusion matrix is a key tool for understanding and evaluating models in supervised classification problems. Various matrices are proposed depending on the problem framework: single-label, multi-label, or even soft-label restricted to probability distributions. …”
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Strength prediction of ECC-CES columns under eccentric compression using adaptive sampling and ML techniques by Khaled Megahed

“…An adaptive sampling process was employed to efficiently explore the design space, resulting in a database of 2,908 FE models. Subsequently, six machine learning models were used to predict the eccentric compressive capacity based on the generated FE database. …”
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Enhanced securities investment strategy using ISSA–SVM: a hybrid model combining adaptive moving average, support vector machine, and multi-strategy sparrow search algorithm for im... by Wei Ni, Qingqing Chen, Xiaochen Guo, Yanan Liu

“…This study proposes a novel hybrid strategy, ISSA–SVM, that combines Adaptive Moving Average (AMA), Support Vector Machine (SVM), and an Improved Sparrow Search Algorithm (ISSA) to enhance CTA model performance in securities investment. …”
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Data‐driven prediction of prolonged air leak after video‐assisted thoracoscopic surgery for lung cancer: Development and validation of machine‐learning‐based models using real‐worl... by Saori Tou, Koutarou Matsumoto, Asato Hashinokuchi, Fumihiko Kinoshita, Hideki Nakaguma, Yukio Kozuma, Rui Sugeta, Yasunobu Nohara, Takanori Yamashita, Yoshifumi Wakata, Tomoyoshi Takenaka, Kazunori Iwatani, Hidehisa Soejima, Tomoharu Yoshizumi, Naoki Nakashima, Masahiro Kamouchi

“…This study aimed to develop and validate a machine‐learning‐based model for predicting clinical outcomes using real‐world data from an electronic clinical pathway (ePath) system. …”
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Fair Probabilistic Multi-Armed Bandit With Applications to Network Optimization by Zhiwu Guo, Chicheng Zhang, Ming Li, Marwan Krunz

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Drilling Parameter Control Based on Online Identification of Drillability and Multi-Objective Optimization by Jianbo Dai, Xilu Yin, Yan Zhang, Lei Si, Dong Wei, Zhongbin Wang, Longmei Zhao

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AutoRL-Sim: Automated Reinforcement Learning Simulator for Combinatorial Optimization Problems by Gleice Kelly Barbosa Souza, André Luiz Carvalho Ottoni

“…Furthermore, parameter optimization is performed using response surface models. …”
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Predicting Short-Range Weather in Tropical Regions Using Random Forest Classifier by Sellappan Palaniappan, Rajasvaran Logeswaran, Anitha Velayutham, Bui Ngoc Dung

“…In this paper, we present a Random Forest classifier machine learning model for predicting short-range weather in in tropical regions like Malaysia. …”
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Prediction and mapping of leaf water content in Populus alba var. pyramidalis using hyperspectral imagery by Zhao-Kui Li, Hong-Li Li, Xue-Wei Gong, Heng-Fang Wang, Guang-You Hao

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Advancing Nutritional Status Classification With Hybrid Artificial Intelligence: A Novel Methodological Approach by Md. Moddassir Alam, Asif Irshad Khan, Aasim Zafar, Mohammad Sohail, Mohammad Tauheed Ahmad, Rezaul Azim

“…The EGBF model is employed to classify nutritional states, including stunting, wasting, severe wasting, overweight, and underweight, providing a robust framework for predictive analysis. …”
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Markov prediction based handover in dynamic ultra dense network by Qingmin MENG, Yuanyuan ZHAO, Wenjing YUE, Yulong ZOU, Xiaoming WANG

“…In order to solve the problem of the communication and computational problems of large-scale machine communication in an ultra-dense cellular network,a Markov prediction based handover scheme (MPHS) was proposed.Firstly,a kind of heterogeneous network design with semi-structure and central control was considered which contains the densely deployed virtual nodes and thus realized a low cost and efficient coverage.The network can dynamically adjust the access point according to the user's mobility and network traffic.Secondly,a Markov model was constructed,and the idea of load-aware was introduced.By weighing the signal quality and the cell load,the user's next optimal access point was effectively predicted.The simulation results show the feasibility and effectiveness of the proposed scheme for cell handover predicting.…”
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Wear Prediction and Visual Decision Support of Drop Forged Rivetless Chain for Conveyors by Liu Manxian, Xu Zijia, Shen Xujia, Li Xiaodong, Zhang Zhijun, Yang Yi

“…In order to accurately detect, predict and maintain the wear condition of drop forged rivetless chain for conveyors, the methods of wear prediction and active maintenance are developed based on gray model and visual decision support. The wear data are acquired by wear detection device based on machine vision. …”
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Addressing water scarcity challenges through rainwater harvesting: A comprehensive analysis of potential zones and model performance in arid and semi-arid regions–A case study on P... by Subhra Halder, Suddhasil Bose

“…This study focuses on tackling this challenge by identifying and classifying rainwater harvesting zones based on their potentiality and comparing the performance of two machine learning models, Artificial Neural Network (ANN) and Random Forest (RF), for optimizing rainwater harvesting strategies. …”
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Biobjective Scheduling for Joint Parallel Machines with Sequence-Dependent Setup by Taking Pareto-Based Approach by Wichai Srisuruk, Kanchala Sudtachat, Paramate Horkaew

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