Determining the Boundaries of Overlying Strata Collapse Above Mined-Out Panels of Zhomart Mine Using Seismic Data by Sara Istekova, Alexander Makarov, Dina Tolybaeva, Arman Sirazhev, Kuanysh Togizov

“…The deliverables may be used to improve the process of recognizing specific types of technogenic heterogeneities in the rock mass, impacting the efficiency and safety of subsurface ore mining, both for localization and mining monitoring.…”
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Combining Process Mining and Process Simulation in Healthcare: A Literature Review by Evelyn Salas, Michael Arias, Santiago Aguirre, Eric Rojas

“…For example, the compilation of case studies in relation to medical fields that have been historically overlooked, and the availability of software that integrates PM and PS, in addition to the extent to which the usefulness of this combination may improve as a result in the field of healthcare.…”
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Clinical application and immune infiltration landscape of stemness‐related genes in heart failure by Wenting Yan, Yanling Li, Gang Wang, Yuan Huang, Ping Xie

“…Feature selection was performed using two machine learning algorithms. Nomogram models were then constructed to predict HF risk based on the selected key genes. …”
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Intensive Care for Anaphylaxis in Children: Current Trends by Yu. V. Bykov, A. N. Obedin, V. V. Fischer, E. V. Volkov, O. V. Zinchenko

“…Knowledge and timely implementation of modern care algorithms for anaphylaxis in children and adolescents will improve the quality of emergency care and reduce the risk of fatal outcomes in this pathology.…”
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What If VEC Is Moving: Probabilistic Model of Task Execution Through Offloading in Vehicular Computing Environments by Asmaa Ibrahim, Bassem Mokhtar

“…Numerous algorithms have been suggested to address these challenges and provide an effective task-offloading framework. …”
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Modality-based Modeling with Data Balancing and Dimensionality Reduction for Early Stunting Detection by Yohanes Setiawan, Mohammad Hamim Zajuli Al Faroby, Mochamad Nizar Palefi Ma’ady, I Made Wisnu Adi Sanjaya, Cisa Valentino Cahya Ramadhani

“…Modality-based modeling, which integrates image and tabular data, can provide a more holistic view and improve detection accuracy. This research aims to analyze modality-based modeling for the early detection of stunting. …”
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Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review by Dhekre Saber Saleh, Mohd Shahizan Othman

“…Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. …”
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Sulfur fumigation of botanical drugs: impact on chemical composition and pharmacological properties, and advances in detection technologies by Weiyi Xu, Hongyu Jin, Ying Wang, Feng Wei, Jing Liu

“…In recent years, researchers have created various innovative detection technologies, including fluorescent probe rapid detection methods and machine learning algorithms, to improve the precision of identifying and quantifying chemical changes in sulfur-fumigated samples. …”
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Ensemble stacked model for enhanced identification of sentiments from IMDB reviews by Komal Azim, Alishba Tahir, Mobeen Shahroz, Hanen Karamti, Annia Almeyda Vazquez, Angel Rojas Vistorte, Imran Ashraf

“…The use of the synthetic minority oversampling technique (SMOTE) is observed to improve the performance and lead to 92.77% accuracy.…”
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BRIDGING THE GAP: OPPORTUNITIES, CHALLENGES AND STRATEGIES FOR AI DEPLOYMENT IN PUBLIC SERVICE DELIVERY by Richard Douglas Kamara

“…By providing a detailed analysis of the advantages and potential challenges, and by suggesting effective implementation strategies, the study seeks to improve governance practices in the digital era, promoting fairness and inclusivity.…”
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Comprehensive evaluation of machine learning models for predicting the cognitive status of Alzheimer's disease subjects and susceptible by Lucien Gnegne Meteumba, Vaghawan Prasad Ojha, Shantia Yarahmadian

“…Overall, this work shows us how machine learning can aid in the understanding of Alzheimer disease and its identification by offering an important means to improve patient outcomes through early treatment strategies based on predictive analytics.…”
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Factors influencing the spatial distribution of police stops and their efficacy in crime prevention and control by Zhuoying Fan, Xuewei Zhang, Guangwen Song, Chunxia Zhang

“…The space is partitioned using hierarchical clustering after applying the XGBoost and SHAP algorithms to determine the factors related to police stops. …”
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Enhanced gap-filling for satellite-derived crop monitoring using temperature-driven reconstruction techniques by Flavian Tschurr, Lukas Valentin Graf, Achim Walter, Helge Aasen

“…Consequently, it has significant potential to improve the reliability of crop productivity assessments based on remote sensing data.…”
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Development and validation of a risk prediction model for depression in patients with chronic obstructive pulmonary disease by Tong Feng, PeiPei Li, Ran Duan, Zhi Jin

“…It offers a valuable tool for early screening and personalized care, with potential to improve mental health outcomes in this population.…”
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Classification of Structural and Functional Development Stage of Cardiomyocytes Using Machine Learning Techniques by V. R. Bondarev, K. O. Ivanko, N. G. Ivanushkina

“…Histogram equalization technique is used to enhance the contrast and dynamic range of the confocal microscopic images with the method of contrast-limited adaptive equalization. This helped to improve the local contrast of the analyzed images and highlight the main elements of the cardiomyocyte. …”
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Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…A lack of more extensive and consistent datasets was the most common issue, followed by the need to improve existing models.…”
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Time Frequency Analysis Based Fault Detection in PV Array Using Scaling Basis Chirplet Transform by S Ramana Kumar Joga, Chidurala SaiPrakash, Srikanth Velpula, Alivarani Mohapatra, Theophilus A. T. Kambo Jr.

“…The early detection of faults in PV arrays is vital to prevent further damage, improve maintenance strategies, and ensure uninterrupted energy production. …”
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Intrusion Detection System Framework for SDN-Based IoT Networks Using Deep Learning Approaches With XAI-Based Feature Selection Techniques and Domain-Constrained Features by Manlaibaatar Tserenkhuu, Md Delwar Hossain, Yuzo Taenaka, Youki Kadobayashi

“…This study proposes an IDS framework to detect various cyberattacks in SDN-based IoT networks utilizing three deep learning algorithms that incorporate hyperparameter tuning and the feature selection process based on explainable artificial intelligence (XAI), which uses domain-constrained features to improve performance and reduce computational complexity. …”
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Spatiotemporal Gap‐Filling of NASA Deep Blue Satellite Aerosol Optical Depth Over the Contiguous United States (CONUS) Using the UNet 3+ Architecture by Jeffrey S. M. Lee, S. Marcela Loría‐Salazar, Heather A. Holmes, Andrew M. Sayer

“…Abstract Due to sensor and algorithmic constraints, satellite aerosol optical depth (AOD) retrievals are spatially incomplete and have gaps caused by clouds and bright surfaces. …”
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Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data by Md Jobair Bin Alam, Ashish Gunda, Asif Ahmed

“…The ability to infer these variables through a singular measurable soil property, soil resistivity, can potentially improve sub-surface characterization. This research leverages various machine learning algorithms to develop predictive models trained on a comprehensive dataset of sensor-based soil moisture, matric suction, and soil temperature obtained from prototype ET covers, with known resistivity values. …”
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