Structural insights into SOD1: from in silico and molecular dynamics to experimental analyses of ALS-associated E49K and R115G mutants by Seyed Mahdi Hosseini Faradonbeh, Bagher Seyedalipour, Nasrin Keivan Behjou, Kimiya Rezaei, Payam Baziyar, Saman Hosseinkhani

“…Our analysis was performed through multiple algorithms on the structural characterization of the hSOD1 protein using computational predictions, molecular dynamics (MD) simulations, and experimental studies to understand the effects of amino acid substitutions. …”
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In Silico Analysis of Coding/Noncoding SNPs of Human RETN Gene and Characterization of Their Impact on Resistin Stability and Structure by Lamiae Elkhattabi, Imane Morjane, Hicham Charoute, Soumaya Amghar, Hind Bouafi, Zouhair Elkarhat, Rachid Saile, Hassan Rouba, Abdelhamid Barakat

“…Stability analysis predicted 9 nsSNPs (I32S, C51Y, G58E, G58R, C78S, G79C, W98C, C103G, and C104Y) which can decrease protein stability with at least three out of the four algorithms used in this study. …”
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Comparative review of intelligent structural safety in building seismic risk mitigation utilizing an integrated artificial intelligence controller by Normaisharah Mamat, Rawad Abdulghafor, Sherzod Turaev, Fitri Yakub

“…The research highlights the influence of integrated AI controllers on control systems, examining several AI controllers, including machine learning algorithms, neural networks, and evolutionary algorithms concerning structural safety. …”
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A manganese metabolism-related gene signature stratifies prognosis and immunotherapy efficacy in kidney cancer by Yang Liu, Hao Ye, Ruoxuan Zhang, Xiaolong Liu, Ranlu Liu

“…Through integrated bioinformatics approaches, including differential expression analysis, univariate Cox regression, and three machine learning algorithms (Boruta, GBM, and RFS), we identified prognosis-related MMCG. …”
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Modeling residue formation from crude oil oxidation using tree-based machine learning approaches by Mohammad-Reza Mohammadi, Seyyed-Mohammad-Mehdi Hosseini, Behnam Amiri-Ramsheh, Saptarshi Kar, Ali Abedi, Abdolhossein Hemmati-Sarapardeh, Ahmad Mohaddespour

“…Four advanced tree-based machine learning algorithms comprising gradient boosting with categorical features support (CatBoost), light gradient boosting machine (LightGBM), random forest (RF), and extreme gradient boosting (XGBoost) were utilized to develop accurate predictive models. …”
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Combined Allocation of Renewable-Based Distributed Generators and Shunt Capacitor Banks in Distribution Networks with Electric Vehicle Load Penetration by Abhilasha Pawar, Rajkumar Viral, Divya Asija, Mohit Bansal

“…Compared to other optimization algorithms, the APO shows superior performance. …”
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Transitional Grid Maps: Joint Modeling of Static and Dynamic Occupancy by Jose Manuel Gaspar Sanchez, Leonard Bruns, Jana Tumova, Patric Jensfelt, Martin Torngren

“…Autonomous agents rely on sensor data to construct representations of their environments, essential for predicting future events and planning their actions. …”
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Artificial intelligence in personalized cardiology treatment by Abbas Mohammadi, Sheida Shokohyar

“…This study examines the advancements and challenges in personalized cardiovascular medicine, highlighting the need to address issues such as data privacy, algorithmic bias, and accessibility to promote the equitable application of personalized medicine.…”
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Liquid white box model as an explainable AI for surgery by Homer A. Riva-Cambrin, Rahul Singh, Sanju Lama, Garnette R. Sutherland

“…Artificial intelligence shows great promise in filling the gap where humans and classical computing algorithms cannot process information in an efficient manner. …”
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Magnetic resonance imaging of cruciate ligament disorders: current updates by Tanda Yang, Yexin Li, Longtao Yang, Qian Liu

“…AI plays a crucial role in automating radiological estimations and enabling data-driven predictions of future events. Despite the transformative impact of advanced MRI techniques on the analytical and diagnostic algorithms related to cruciate ligament disorders, future efforts are warranted to address challenges such as economic burdens and ethical considerations.…”
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A critical assessment of ionic liquid-based aqueous biphasic systems for biomolecules extraction and CO2 absorption by Viggy Wee Gee Tan, Yazan Abuhasheesh, Doris Ying Ying Tang, Yongyu Zhang, Zengling Ma, Lin Chen, Rambabu Krishnamoorthy, Pau Loke Show

“…The incorporation of machine learning (ML) algorithms to predict the toxicity and CO2 capture properties, as well as the scaling up of IL-ABSs, is also explored.…”
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UNVEILING FAKE NEWS DETECTION MODELS AND THEIR INTEGRATION INTO WEB SYSTEMS: AN EXTENSIVE INVESTIGATION by Vimal Gaur, Naman Veerwal, Ujjwal Chaudhary, Sparsh Kadian

“…Powered by Multinomial Naive Bayes and Passive Aggressive Classifier algorithms, Fake News Detection System ensures accurate classification. …”
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Echo state networks for modeling turbulent convection by Mohammad Sharifi Ghazijahani, Christian Cierpka

“…Meanwhile, Echo State Networks (ESN) are among the most fundamental machine learning algorithms suited for modeling sequential data. The current study conducts reduced order modeling of experimental RBC. …”
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Multimodal Deep Learning for Android Malware Classification by James Arrowsmith, Teo Susnjak, Julian Jang-Jaccard

“…We synthesise these modalities by combining predictions from convolutional and graph neural networks with a multilayer perceptron. …”
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Immune microenvironment and prognostic genes of triple-negative breast cancer in the context of transcriptome and single-cell sequencing by Xiangqin Huang, Wei Chen, Zhiwu Lin, Hui Zhang, Ruijuan Wang, Cailing Lin

“…Differential expression analysis, univariate Cox regression, and machine learning algorithms identified BPI, GPHA2, KIR3DL3, MASP1, RASGRP1, and SEMA4A as potential prognostic genes. …”
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Post-Pandemic Urban Future: Identification of the main trends of change in Latin America, through the application of the Delphi method by Yeimis Milton Palomino Pichihua

“…Additionally, it employs machine learning algorithms to transform them into predictions. The sample is made up of 26 panelists from different Latin American countries, who participated in successive questionnaires until stable results were reached. …”
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An Approximate Bayesian Inference for Beta Regression Models by kobra Gholizadeh Gazvar, Mohsen Mohammadzadeh

“…Bayesian analysis of these models generally requires the calculation of multiple integrals. The use of MCMC algorithms sometimes encounters long computation times and divergence. …”
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CROWD MONITORING AND CONTROLLING SYSTEM FOR HOMELAND SECURITY IMPROVEMENT by Ahmad Abubakar Mustapha, Mohamed Sirajudeen Yoosuf

“…This device offers a proactive approach to security monitoring, enabling swift responses to predict weapons and emotions in a crowd's suspicious activities and enhancing overall situational awareness.…”
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Innovative approaches to optimizing the road safety monitoring system by Shevtsova A.G., Bychkova C.A., Podkopaev A.V., Nechaev O.Y.

“…The article presents a statistical analysis of innovative approaches to optimizing the system for monitoring the level of accidents and social risk, which is aimed at improving the predictive capabilities of the existing system for monitoring road safety indicators on the State Traffic Safety Inspectorate website. …”
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Comparison of Recognition Techniques to Classify Wear Particle Texture by Mohammad Laghari, Ahmed Hassan, Mahmoud Haggag, Addy Wahyudie, Motaz Tayfor, Abdallah Elsayed

“…This analysis plays a vital role in predictive maintenance by revealing component degradation in machinery. …”
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