Development, deployment, and feature interpretability of a three-class prediction model for pulmonary diseases by Zhenyu Cao, Gang Xu, Yuan Gao, Jianying Xu, Fengjuan Tian, Hengfeng Shi, Dengfa Yang, Zongyu Xie, Jian Wang

“…Features with p < 0.05 from univariate analyses were selected using the Boruta algorithm for input into Random Forest (RF) and XGBoost models. …”
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Developing a predictive model for septic shock risk in acute pancreatitis patients using interpretable machine learning algorithms by Binglin Song, Ping Liu, Kangrui Fu, Chun Liu

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Developing Shuffled Frog-Leaping Algorithm (SFLA) Method to Solve Power Load-Constrained TCRTO Problems in Civil Engineering by Xingyu Tao, Heng Li, Chao Mao, Chen Wang, Jeffrey Boon Hui Yap, Samad Sepasgozar, Sara Shirowzhan, Timothy Rose

“…This study aims to develop a modified shuffled frog-leaping algorithm (SFLA) approach in project scheduling to aid decision-makers in identifying the best Pareto solution for time-cost-resource trade-off (TCRTO) problems under the constraint of precedence, resource availability, and on-site peak electricity power load. …”
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iFQS: An Integrated FCNP-Q-Learning-Based Scheduling Algorithm for On-Demand Charging in Wireless Rechargeable Sensor Networks by Man Gun Ri, Chun Hyok Kim, Se Hun Pak, Chol Min Pong

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Wavelet Transform-Based 3D Landscape Design and Optimization for Digital Cities by Yang Chen, Xiaolin Wang, Chang Zhang

“…The method collects digital city feature information at the information layer and preprocesses the feature information by a rate detection algorithm. Then, LSTM and RBF-BP neural networks in deep learning are used in the feature layer for adaptive learning of multiple feature signals, and finally, fuzzy logic is used to control the system decision output to improve the efficiency of 3D landscape design. …”
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Comparative Evaluation of Mean Cumulative Regret in Multi-Armed Bandit Algorithms: ETC, UCB, Asymptotically Optimal UCB, and TS by Lei Yicong

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Application of 3D Digital Image Processing Technology in Modern Packaging Design by Kun Meng, Fulong Liu

“…In addition, this paper proposes a new target recognition and tracking scheme, which uses the method of servo motor to control the synchronous conveyor belt to monitor the moving objects in real time and proposes a decision analysis algorithm to avoid repeated identification of multiple moving targets. …”
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Assessing the potential of a Bayesian ranking as an alternative to consensus meetings for decision making in research funding: A case study of Marie Skłodowska-Curie actions. by Rachel Heyard, David G Pina, Ivan Buljan, Ana Marušić

“…However, previous research has shown inconsistency in decisions and inefficiency of consensus meetings. Using data from the Marie Skłodowska-Curie Actions, we aimed at investigating the differences between an algorithmic approach to summarise the information from grant proposal individual evaluations to decisions after consensus meetings, and we present an exploratory comparative analysis. …”
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On the optimal control of single-stage hybrid manufacturing systems via novel and different variants of particle swarm optimization algorithm by M. Senthil Arumugam, M. V. C. Rao

“…This paper presents several novel approaches of particle swarm optimization (PSO) algorithm with new particle velocity equations and three variants of inertia weight to solve the optimal control problem of a class of hybrid systems, which are motivated by the structure of manufacturing environments that integrate process and optimal control. …”
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Intrusion Detection-Data Security Protection Scheme Based on Particle Swarm-BP Network Algorithm in Cloud Computing Environment by Zhun Wang, Xue Chen

“…Then, by introducing the decision tree algorithm, the overfitting is reduced and the data processing speed of the model is improved, and on this basis, the feature selection is carried out through the “gain rate” optimization method, which reduces the redundant information of the feature vector. …”
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Retracted: Software solution for text summarisation using machine learning based Bidirectional Encoder Representations from Transformers algorithm by Abdulwahid Al Abdulwahid

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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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Assessing carbon–neutral supercapacitors in renewable energy systems with self-improving agent-based molecular fuzzy intelligent algorithms by Oscar Castillo, Hasan Dinçer, Serkan Yüksel, Serkan Eti

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Synergistic integration of refined pelican optimization algorithm and deep neural networks for autonomous vehicle control in edge computing architectures by Fude Duan, Bing Han, Xiongzhu Bu

“…The chief contributions of the present study have been threefold: (1) the improvement of a particular autonomous driving method optimized for mobile edge computing platforms; (2) the arrangement of an optimized MobileNet method employing the RPO algorithm that uses LiDAR sensor data for effective object recognition and path design; and (3) the construction of an indoor vehicle prototype by mean of a microcontroller and LiDAR sensors, after a comprehensive performance evaluation of inference models, and analyzing the trade-offs between input size and computational effectiveness. …”
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Machine Learning Classification of 3D Intracellular Trafficking Using Custom and Imaris-Derived Motion Features by Oleg Kovtun

“…Although considerable progress has been made, accurately distinguishing between different types of diffusion in three dimensions remains a significant challenge. …”
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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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Robust multi-objective optimization for water flooding under geological uncertainty by Abobakr Sori, Mohammad Sharifi, Nooshin Jabari

“…By employing a multi-objective optimization (MOO) algorithm, we aim to minimize the sensitivity of objective functions to geological variability. …”
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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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Hybrid Feature Selection and Classifying Stages through Electrocardiogram (ECG) Signal for Heart Disease Prediction by Babu Kumar, Radhakrishnan Soundararajan, Kanimozhi Natesan, Roobini Maridhas Santhi

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