Improved Key Microbial Biomarker Discovery Using Ensemble Statistical Methods by Walter Pirovano, Yashjit Gangopadhyay, Mirna Lilian Baak, Christiaan Arie de Leeuw, Radhika Bongoni, Eline Suzanne Klaassens

“…However, advanced biostatistical analysis is required to properly combine microbiome taxonomic abundance data with phenotypical metadata and reliably predict disease states. While differential abundance analysis and machine-learning techniques are widely used to perform such analyses, selecting the best method is not trivial due to the complexity and specific characteristics of both the data and the algorithms. …”
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Mathematical Modelling and Optimisation of Operating Parameters for Enhanced Energy Generation in Gas Turbine Power Plant with Intercooler by Anthony O. Onokwai, Udochukwu B. Akuru, Dawood A. Desai

“…The RSM, being the initial model, was able to predict but lacked precision when compared with the nonlinear influences that were modelled by ANFIS PSO and ANFIS GA, with power output, thermal efficiency and specific fuel consumption (sfc) having corresponding R² values of 0.979, 0.987 and 0.972. …”
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Two General Data Protection Regulation (GDPR) Compliant Approaches to Scoring Firm Financial Frailty in Business Litigation by A. E Rodriguez, Gazi Murat Duman, Ron Kuntze

“…We then map the scores onto bivariate classes using Fisher-Jenks clustering. Each algorithm’s accuracy is obtained by comparing its predictions of either failure of viability to those of the labeled data in O'Haver (1993). …”
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Web Application for Mathematical Modeling of Unsteady Oil Flow in Porous Medium by A. A. Mazitov

“…It is applicable for studying fluid dynamic processes and can be used to predict flowrates, production and calculation of optimal well operation modes.Discussion and Conclusion. …”
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Tuning of PID Controller for Speed Control of DC-Motor by using Generalized Regression Neural Network and Invasive Weed Optimization by Muhammad Hilal, Haider TH. Salim ALRikabi, Ibtisam A. Aljazaery

“…To optimize motor drive speed using GRNN and IWO algorithms, data on motor performance over time must be collected and used to train a GRNN model that can predict future motor performance based on past performance. …”
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Proximal remote sensing of dissolved organic matter in aqua-culture ponds via multi-temporal spectral correction by Wenxu Lv, Yancang Wang, Huiqiong Cao, Peng Cheng, Xiaohe Gu, Zhuoran Ma, Mengjie Li, Ruiyin Tang, Qichao Zhao, Xuqing Li, Lan Zhang, Shuaifei Liu

“…Compared with the original spectrum, an average R2 improvement of 30.67%, along with reductions of 17% in RMSE and 11.67% in MAE. Among the three algorithms, the Random Forest model yielded the best performance, with an R2 of 0.82, RMSE of 3.1 mg/L, and MAE of 2.37 mg/L on the test set. …”
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Cancer Patients Missing Pain Score Information:- Application with Imputation Techniques by Gajendra Vishwakarma, Atanu Bhattacharjee, Jesna Jose, Ramesh V

“…Interpretation and Conclusion: The EM algorithm shows the least percentage change from observed values in both visits followed by predictive mean matching method and MCMC methods. …”
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A recurrent neural network‐based rotor displacement estimation method for eight‐pole active magnetic bearing by Longyuan Fan, Zicheng Liu, Haijiao Wang, Dong Jiang, Yu Chen

“…The input dimensions and the architecture of the neural network are optimised to improve both prediction accuracy and computational complexity. Experimental results validate the effectiveness of the algorithm and demonstrate that the proposed method has high accuracy, robustness and generalisation ability.…”
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MicroRNA-1912 regulates cholesterol homeostasis by targeting PCSK9 by Chan Joo Lee, Myeongjune Go, Sae-Bom Jeon, Sun-Ho Lee, Dongkook Min, So Hee Park, Seunghyun Lee, Sahng Wook Park

“…Specific interactions of miR-1912 and miR-224 with the 3′ untranslated region (UTR) of PCSK9 mRNA were confirmed by a luciferase reporter assay and site-directed mutagenesis analysis of the predicted seed region. In transgenic mice expressing liver-specific human PCSK9 with its 3ʹ UTR, administration of miR-1912 mimics resulted in a reduction of plasma total cholesterol levels as determined by fast protein liquid chromatography following hepatic delivery. …”
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Gait-Based AI Models for Detecting Sarcopenia and Cognitive Decline Using Sensor Fusion by Rocío Aznar-Gimeno, Jose Luis Perez-Lasierra, Pablo Pérez-Lázaro, Irene Bosque-López, Marina Azpíroz-Puente, Pilar Salvo-Ibáñez, Martin Morita-Hernandez, Ana Caren Hernández-Ruiz, Antonio Gómez-Bernal, María de la Vega Rodrigalvarez-Chamarro, José-Víctor Alfaro-Santafé, Rafael del Hoyo-Alonso, Javier Alfaro-Santafé

“…Finally, machine learning models were developed using these variables to predict sarcopenia and CD. <b>Results</b>: Models based on sensor data, CV data, and a combination of both technologies achieved high predictive accuracy, particularly for CD. …”
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Evaluation of liver fibrosis in patients with metabolic dysfunction-associated steatotic liver disease using ultrasound controlled attenuation parameter combined with clinical feat... by LIU Chunyu, TANG Jingkuan, ZHAO Wei

“…Features were selected using the Boruta algorithm, and a predictive model combining CAP and clinical features was constructed. …”
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LimeSoDa: A dataset collection for benchmarking of machine learning regressors in digital soil mapping by Jonas Schmidinger, Sebastian Vogel, Viacheslav Barkov, Anh-Duy Pham, Robin Gebbers, Hamed Tavakoli, Jose Correa, Tiago R. Tavares, Patrick Filippi, Edward J. Jones, Vojtech Lukas, Eric Boenecke, Joerg Ruehlmann, Ingmar Schroeter, Eckart Kramer, Stefan Paetzold, Masakazu Kodaira, Alexandre M.J.-C. Wadoux, Luca Bragazza, Konrad Metzger, Jingyi Huang, Domingos S.M. Valente, Jose L. Safanelli, Eduardo L. Bottega, Ricardo S.D. Dalmolin, Csilla Farkas, Alexander Steiger, Taciara Z. Horst, Leonardo Ramirez-Lopez, Thomas Scholten, Felix Stumpf, Pablo Rosso, Marcelo M. Costa, Rodrigo S. Zandonadi, Johanna Wetterlind, Martin Atzmueller

“…We demonstrated the use of LimeSoDa for benchmarking by comparing the predictive performance of four learning algorithms across all datasets. …”
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Long-term prognosis of 47 pediatric patients with Blau syndrome in China by Xinwei Shi, Jianghong Deng, Junmei Zhang, Xiaozhen Zhao, Yinan Zhao, Li Li, Fengqiao Gao, Weiying Kuang, Jiang Wang, Xiaohua Tan, Chao Li, Shipeng Li, Caifeng Li

“…A Bayesian network was constructed to integrate prediction algorithms of genetic mutations and clinical manifestations, exploring the complex relationship between genotype and phenotype through R (Version 4.4.1, R Core Development Team). …”
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Detecting Botrytis Cinerea Control Efficacy via Deep Learning by Wenlong Yi, Xunsheng Zhang, Shiming Dai, Sergey Kuzmin, Igor Gerasimov, Xiangping Cheng

“…The innovations include (1) combining channel attention mechanism, multi-head self-attention mechanism, and multi-scale feature extractor to improve prediction accuracy and (2) introducing the Shapley value algorithm to achieve a precise quantitative analysis of environmental variables’ contribution to colony growth. …”
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Learning atomic forces from uncertainty-calibrated adversarial attacks by Henrique Musseli Cezar, Tilmann Bodenstein, Henrik Andersen Sveinsson, Morten Ledum, Simen Reine, Sigbjørn Løland Bore

“…While already providing great practical value, little is known about the actual prediction errors of MLIPs on adversarial structures and whether these errors can be controlled. …”
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PATH CONTROL AIRCRAFT OF TRAJECTORY UNDER THE INFLUENCE OF DISTURBANCES ON AN DUAL CHANNEL by S. A. Kabanov, F. V. Mitin

“…The problem is solved using the algorithm with the predictive model.…”
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Experimental acoustic study of small horizontal axis wind turbines based on computational fluid dynamics and artificial intelligence approaches by M. Sadeghi malekabadi, A.R. Davari

“…Comparisons between CFD results and NN predictions validate the accuracy of the neural network. …”
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Using Time Clusters for Following Users’ Shifts in Rating Practices by Dionisis Margaris, Costas Vassilakis

“…In that sense, the practice of using a single mean value for adjusting users’ ratings is inadequate, since it fails to follow such shifts in users’ rating practices, leading to decreased rating prediction accuracy. In this work, we address this issue by using the concept of dynamic averages introduced earlier and we extend earlier work by (1) introducing the concept of rating time clusters and (2) presenting a novel algorithm for calculating dynamic user averages and exploiting them in user-user collaborative, filtering implementations. …”
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Detection of Aflatoxin B1 in Maize Silage Based on Hyperspectral Imaging Technology by Lina Guo, Haiqing Tian, Daqian Wan, Yang Yu, Kai Zhao, Xinglu Zheng, Haijun Li, Jianying Sun

“…Among the models, SVR_SD_Mixup_PCA achieved the best performance, with an <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi mathvariant="normal">R</mi></mrow><mrow><mi mathvariant="normal">p</mi></mrow><mrow><mn>2</mn></mrow></msubsup></mrow></semantics></math></inline-formula> of 0.9458, RMSEP of 3.1259 μg/kg, and RPD of 4.2969, indicating high prediction accuracy and generalization capability. This study fills the gap of hyperspectral image technology fused with artificial intelligence algorithm in the application of quantitative detection of AFB1 content in maize silage and provides a new technical method and theoretical basis for nondestructive testing of corn silage feed.…”
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Risk Limiting Based Resilient Operation Method for Power Grid by Xiyue WANG, Hao ZHANG, Chaoyi PENG

“…Finally, based on the IEEE 6-node system and an actual 25981-node regional grid examples, we analyze the relationship between system flexibility, prediction accuracy, and system resilience, and it is concluded that improving the operational resilience of the new power system is premised on sufficient system flexibility and prediction accuracy.…”
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