Identification of the immune infiltration and biomarkers in ulcerative colitis based on liquid–liquid phase separation-related genes by Zhixing Hong, Shilin Fang, Haihang Nie, Jingkai Zhou, Yuntian Hong, Lan Liu, Qiu Zhao

“…We identified the hub LLPS-RGs (DE-LLPS-RGs) (HSPB3, SLC16A1, TRIM22, SRI, PLEKHG6, GBP1, PADI2) by machine learning algorithms. Hub genes were screened that displayed high prediction accuracy of UC patients. …”
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Assessment of seasonal variations in the air quality index (2019–2022) in Al-Jahra city, Kuwait by Alsowaidan S., Al-Hurban A., Alsaber A.

“…An assessment of air quality indices was carried out by using different algorithms models, including random forest (RF), an artificial neural network (ANN), and extreme gradient boosting (XGBoost). …”
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Deep Learning-Driven Geospatial Modeling of Elderly Care Accessibility: Disparities Across the Urban-Rural Continuum in Central China by Yi Yu, Tian Dong

“…Spatial weighting characteristics of elderly care facility locations were analyzed through machine learning algorithms, and service coverage disparities between urban districts and suburban towns were assessed under 5-, 10-, and 15-min walking thresholds. …”
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Discovery, design, and engineering of enzymes based on molecular retrobiosynthesis by Ancheng Chen, Xiangda Peng, Tao Shen, Liangzhen Zheng, Dong Wu, Sheng Wang

“…We first introduce the molecular retrosynthesis route planning in biochemical pathway design, including single‐step retrosynthesis algorithms and AI‐based chemical retrosynthesis route design tools. …”
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Macro-microscopic study on the damage threshold strain of particle-filled polymer composites by Wang Jiaxiang, Qiang Hongfu, Wang Xueren, Wang Zhejun, Li Shiqi

“…Subsequently, optimization algorithms were used to determine the parameter values in the model, and the effectiveness of the model was compared and verified. …”
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Color image reversible data hiding based on adaptive capacity allocation and pixel value similarity distance sorting by Ningxiong Mao, Chunping Ouyang, Yaping Wan, Lingfeng Qu, Yuan Yuan

“…Abstract Most existing reversible data hiding (RDH) algorithms for color images adopt a fixed-ratio capacity allocation approach, often resulting in allocation errors. …”
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Integrated bioinformatics, machine learning, and molecular docking reveal crosstalk genes and potential drugs between periodontitis and systemic lupus erythematosus by Junjie Wang, Qingao Deng, Lu Qi

“…The resulting diagnostic models demonstrated robust efficacy in both training and validation datasets. Four topological algorithms in Cytoscape highlighted four central crosstalk genes (TAGLN, MMP9, TNFAIP6, IL1B). …”
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Evaluating the Thermohydraulic Performance of Microchannel Gas Coolers: A Machine Learning Approach by Shehryar Ishaque, Naveed Ullah, Sanghun Choi, Man-Hoe Kim

“…Furthermore, advanced machine learning algorithms such as extreme gradient boosting (XGB), random forest (RF), support vector regression (SVR), k-nearest neighbors (KNNs), and artificial neural networks (ANNs) were employed to analyze their predictive capability. …”
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Radiomic Feature Extraction Based on Computed Tomography for Stroke Patients by Alamgir Hossain, Jolly Sultana, Shahed Hossain, Hafizur Rahman

“…To improve diagnosis, classification, and prediction for the best possible patient outcomes, this study investigates how radiomics might improve computed tomography (CT)-based stroke evaluation. …”
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Structural Magnetic Resonance Imaging Brain Age Investigation in Athletes with Persistent Postconcussion Syndrome by Samuel Guay, Camille Charlebois-Plante, Sophie-Andrée Vinet, Marie-Eve Bourassa, Louis De Beaumont

“…Brain age prediction algorithms using structural magnetic resonance imaging (MRI) estimate the biological age of the brain by comparing it to a normal aging trajectory, allowing for the identification of deviations that may indicate slower or accelerated biological aging. …”
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State of Charge Estimation in Li-Ion Batteries Using a Parallel LSTM-Based Approach: The Impact of Modeling Based on Operating States by Osman Ozer, Hayri Arabaci

“…To address this, deep learning algorithms such as long short-term memory (LSTM) have been focused on for SOC prediction. …”
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Revolutionizing Marine Stability: A Review of Cutting-Edge Gyro Stabilizer Designs and Techniques for Vessels by Wan Rahiman, Mohamad Hazwan Mohd Ghazali, Iskandar Al-Thani Mahmood

“…Despite these challenges, recent advancements in control algorithms and optimization techniques have improved gyro stabilizer adaptability under varying sea conditions. …”
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Development of a Wireless Sensor Network and IoT-based Smart Irrigation System by Juliana Ngozi Ndunagu, Kingsley Eghonghon Ukhurebor, Moses Akaaza, Robert Birundu Onyancha

“…The sample size used contains 5722 rows and 6 columns from the result of our machine learning algorithms using Microsoft Excel and Jupyter Notebook to process and evaluate the performance of the drip SIS, considering the soil moisture, soil temperature, sunlight, rain, and pump. …”
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Evaluation of Smart Building Integration into a Smart City by Applying Machine Learning Techniques by Mustafa Muthanna Najm Shahrabani, Rasa Apanaviciene

“…The existing literature on assessment methodologies reveals diverging evaluation frameworks for smart buildings and smart cities, non-uniform metrics and taxonomies that hinder scalability, and the low use of machine learning in predictive integration modelling. To fill these gaps, this paper introduces a novel machine learning model to predict smart building integration into smart city levels and assess their impact on smart city performance by leveraging data from 147 smart buildings in 13 regions. …”
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The Role of Intelligent Transport Systems and Smart Technologies in Urban Traffic Management in Polish Smart Cities by Ewa Puzio, Wojciech Drożdż, Maciej Kolon

“…The study uses a mixed-method approach, including the analysis of crowdsourced mobility data (from GPS, smartphones, and municipal reports), GIS tools for mapping congestion, big data analytics, and machine learning algorithms, to evaluate trends and predict traffic scenarios. …”
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Workload Forecasting Methods in Cloud Environments: An Overview by Samah Aziz, Manar Kashmoola

“…In this study, we discuss some methods of predicting workload in cloud environments. This study presents an overview of workload prediction techniques in cloud systems, with a special emphasis on long short-term memory (LSTM) networks. …”
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Dynamic Processes of Development Jointing of a Fractal Type: Models for a Solid-State Material of the Chamber in a Power Facility during its Operation by T. V. Ryzhova, D. N. Bukharov, M. M. Arakelyan, S. M. Arakelyan

“…The availability of a reliable database of their characteristics and operating modes of the working substance in real conditions with numerical parameters should allow, within the framework of the considered concepts, to fulfil predictive modeling and prediction of the durability of safe and stable operation of such devices and control their modes, taking into account appropriate metrological support.…”
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Identification of biomarkers for the diagnosis in colorectal polyps and metabolic dysfunction-associated steatohepatitis (MASH) by bioinformatics analysis and machine learning by Ying Geng, Yifang Li, Ge Liu, Jian Jiao

“…This study investigated the biomarkers of MASH and colorectal polyps, and the prediction of targeted drugs using an integrated bioinformatics analysis method. …”
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Cooling Load Forecasting Method for Central Air Conditioning Systems in Manufacturing Plants Based on iTransformer-BiLSTM by Xiaofeng Huang, Xuan Zhou, Junwei Yan, Xiaofei Huang

“…Experimental validation on a cooling load dataset from a welding workshop in a manufacturing plant, including ablation studies and comparative analyses with other algorithms, demonstrates that the proposed method achieves superior performance compared to traditional approaches in forecasting accuracy. …”
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Raising Awareness of Acute Kidney Injury: Unfolding the Truth by Aida Lydia

“…Considering the substantial impacts of AKI in ICU patients, early implementation of preventive measures should be an essential program which consists of developing AKI risk stratification in the ICU and encouraging the use of novel AKI biomarkers (TIMP-2, IGFBP-7, Cystatin C, IL-18,  KIM-1 and NGAL) as well as other risk stratification tools (clinical risk prediction scores, computer algorithms, furosemide stress test). …”
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