Monitoring the antibiotic resistance in the intensive care unit of a multidisciplinary hospital by V. Yu. Zemko, V. K. Okulich, A. M. Dzyadz’ko

“…It is necessary to monitor the resistance of common microorganisms to certain antibiotics in order to develop algorithms for rational antibacterial treatment in each hospital.…”
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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid, Hamza Kheddar, Noureddine Batel, Muhammad E. H. Chowdhury

“…These processes begin with capturing speech in analog form and applying signal processing algorithms to ensure compatibility with devices like cochlear implants (CIs). …”
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Unmasking social bots: how confident are we? by James Giroux, Gangani Ariyarathne, Alexander C. Nwala, Cristiano Fanelli

“…Despite the progress made in developing multiple sophisticated social bot detection algorithms and tools, bot detection remains a challenging, unsolved problem that is fraught with uncertainty due to the heterogeneity of bot behaviors, training data, and detection algorithms. …”
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Comprehensive datasets for RNA design, machine learning, and beyond by Jan Badura, Agnieszka Rybarczyk, Tomasz Zok

“…We demonstrated the potential of the dataset by testing it with several popular open-source RNA design algorithms. Furthermore, we illustrated how our dataset can be used to train machine learning models that consider both RNA sequence and structure, potentially advancing RNA design and prediction capabilities.…”
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CECT-Based Radiomic Nomogram of Different Machine Learning Models for Differentiating Malignant and Benign Solid-Containing Renal Masses by Qian L, Fu B, He H, Liu S, Lu R

“…Radiomic features were extracted from the arterial, venous and delayed phases and further analysed by dimensionality reduction and selection. Four mainstream machine learning algorithm training models, namely, support vector machine (SVM), k-nearest neighbour (kNN), light gradient boosting (LightGBM) and logistic regression (LR), were constructed to determine the best classifier model. …”
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Enhanced Projection Method for the Solution of the System of Nonlinear Equations Under a More General Assumption than Pseudo-Monotonicity and Lipschitz Continuity by Kanikar Muangchoo, Auwal Bala Abubakar

“…Some benchmark test problems, which included monotone and pseudo-monotone problems, were considered for the experiments. Lastly, the algorithm was utilized to solve the logistic regression (prediction) model.…”
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Neuro-fuzzy inference system and white shark optimization of coagulation-flocculation of aquaculture wastewater treatment by A.F. Mohamed, H. Rezk

“…The R-squared values for training and testing are 1.0 and 0.82, respectively, and adaptive neuro-fuzzy inference system reduced the root mean square error from 6.8 with analysis of variance to 1.135 with adaptive neuro-fuzzy inference system achieving an 83.5 percent reduction. The R-squared value for prediction rose 7.2 percent from 0.765 via analysis of variance to 0.82 via adaptive neuro-fuzzy inference system.CONCLUSION:  Adaptive neuro-fuzzy inference system succseded to present an accurate model of  wastewater treatment process  and white shark optimizer defined accutrelly the values of chitosan dose, pontential of hydrogen, and settling time to reduce turbidity and salinity. …”
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Impacts of Spatial Expansion of Urban and Rural Construction on Typhoon-Directed Economic Losses: Should Land Use Data Be Included in the Assessment? by Siyi Zhou, Zikai Zhao, Jiayue Hu, Fengbao Liu, Kunyuan Zheng

“…Results demonstrate three key findings: (1) By introducing prototype learning, a meta-learning approach, to guide model updates, we achieved precise assessments with small training samples, attaining an MAE of 1.02, representing 58.5–76.1% error reduction compared to conventional machine learning algorithms. …”
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Research progress on theory and simulation of supercritical CO2 pipeline transportation by Meng LI, Chaofei NIE, Xin OUYANG, Zhenning FAN, Haining LIANG, Jianwu LIU, Zhigang XU, Yan ZHANG

“…Therefore, these models and algorithms need to be modified to incorporate actual engineering data. …”
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Collaborative governance model for spoil disposal and gully infill land creation near open-pit coal mines by Shaogang LEI, Jianying ZHANG, Chang LIU, Liang WANG, Zhenwang JIA

“…The results show that the total area of natural gullies around the open-pit mine treated by this model is 2.588 × 105 m2, reducing the amount of earthwork discharge in the mining area by about 1.536 × 107 m3; By combining the CLiDE geomorphic evolution and soil erosion assessment model, we simulated and evaluated a 66.53% reduction in regional soil erosion after collaborative treatment of surrounding gullies over a 30-year period. …”
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Investigating Spatial Effects through Machine Learning and Leveraging Explainable AI for Child Malnutrition in Pakistan by Xiaoyi Zhang, Muhammad Usman, Ateeq ur Rehman Irshad, Mudassar Rashid, Amira Khattak

“…The use of machine learning algorithms, specifically XGBoost and Random Forest, highlighted the significant role played by the average value in the neighbourhood in predicting childhood stunting in nearby districts, confirming that the spatial spillover effect is not bounded by geographical boundaries. …”
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Gender Disparities in Artificial Intelligence–Generated Images of Hospital Leadership in the United States by Mia Gisselbaek, MD, Joana Berger-Estilita, MD, PhD, Laurens Minsart, MD, Ekin Köselerli, MD, Arnout Devos, PhD, Francisco Maio Matos, PhD, Odmara L. Barreto Chang, MD, PhD, Peter Dieckmann, PhD, Melanie Suppan, MD, Sarah Saxena, MD, PhD

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Least Square Regularized Regression for Multitask Learning by Yong-Li Xu, Di-Rong Chen, Han-Xiong Li

“…The study of multitask learning algorithms is one of very important issues. This paper proposes a least-square regularized regression algorithm for multi-task learning with hypothesis space being the union of a sequence of Hilbert spaces. …”
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Improving Performance of KNN and C4.5 using Particle Swarm Optimization in Classification of Heart Diseases by Pareza Alam Jusia, Abdul Rahim, Herti Yani, Jasmir Jasmir

“…In this research, a comparison was made of the performance of the PSO-based K-NN and C4.5 algorithms. Following experiments employing PSO optimization to improve the K-NN and C4.5 algorithms, the findings indicated that the K-NN algorithm performed exceptionally well with PSO, achieving an accuracy of 89.09%, precision of 89.61%, recall of 90.79%, and an AUC value of 0.935.…”
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Gauge-fixing quantum density operators at scale by Amit Jamadagni, Eugene Dumitrescu

“…We provide a theory, algorithms, and simulations of nonequilibrium quantum systems using a one-dimensional (1D) completely positive (CP), matrix-product (MP) density-operator (ρ) representation. …”
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Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function by Hailun Wang, Daxing Xu

“…Compared with a single kernel function, unscented Kalman filter (UKF) support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.…”
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Environmental performance driven optimization of urban modular housing layout in Singapore by Xiaoyu Shen, Xue Ye

“…It integrates three-dimensional cellular automata, parametric performance simulation, genetic optimization algorithms, and hierarchical clustering algorithms. …”
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Facial expression recognition based on adaptation of the classifier to videos of the user by E.N. Churaev, A.V. Savchenko

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Relationship between intra-bladder pressure and acute kidney injury in patients with acute pancreatitis: interpretable machine learning approach by Gang Liao, Baning Ye, Jianquan Li, Mingxiang Wen

“…Then, the ML algorithm is used to establish the prediction model. …”
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Achieving Closed-Loop Control Simulation of Human-Artefact Interaction: A Comparative Review by Wilhelm Frederik van der Vegte, Imre Horváth

“…For human decision making, however, validated algorithms exist only to predict the timing but not the reasoning behind it. …”
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