QSAR, docking and pharmacokinetic studies of 2,4-diphenyl indenol [1,2-B] pyridinol derivatives targeting breast cancer receptors by Auwal Isa, Adamu Uzairu, umar Umar, Muhammad Tukur Ibrahim, Abdullahi Umar

“…A robust quantitative structure-activity relationship (QSAR) model, developed using genetic algorithms and multilinear regression analysis, predicts chemical activity (pGI50) against breast cancer receptors. …”
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SUMOylation-related genes define prognostic subtypes in stomach adenocarcinoma: integrating single-cell analysis and machine learning analyses by Kaiping Luo, Kaiping Luo, Donghui Xing, Donghui Xing, Xiang He, Yixin Zhai, Yanan Jiang, Hongjie Zhan, Zhigang Zhao

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Machine learning classification of consumption habits of creatine supplements in gym goers by Patrícia C. Magalhães, Samuel Encarnação, Andre C. Schneider, Pedro Forte, José Teixeira, Antonio Miguel Monteiro, Tiago M. Barbosa, Ana M. Pereira

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Machine Learning-Based Analysis of Travel Mode Preferences: Neural and Boosting Model Comparison Using Stated Preference Data from Thailand’s Emerging High-Speed Rail Network by Chinnakrit Banyong, Natthaporn Hantanong, Supanida Nanthawong, Chamroeun Se, Panuwat Wisutwattanasak, Thanapong Champahom, Vatanavongs Ratanavaraha, Sajjakaj Jomnonkwao

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A Data Fusion System for Simulation of Critical Scenarios and Decision-Making by Jimmy Anderson Flórez Zuluaga, Esteban Patino Carrasco, Jose David Ortega Pabón, Kelly Gallego León, O. Lucía Quintero Montoya

“…This document describes an investigation product resulted in a simulation system, based on a combination of fuzzy logic, genetic algorithms and decision trees which let modelled and simulated various entities and their automatic response according to simulated patterns and situations, in which, through operators, decision maker can modify entities behaviour, according to parameterized restrictions and physical conditions. …”
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Collision Avoidance Behavior Mining Model Considering Encounter Scenarios by Shuzhe Chen, Chong Zhang, Lei Wu, Ziwei Wang, Wentao Wu, Shimeng Li, Haotian Gao

“…With the development of intelligent waterborne transportation, mining collision avoidance patterns based on spatiotemporal and motion data of ships are crucial for the autonomous navigation of intelligent ships, which requires accurate collision avoidance information under various encounter scenarios. …”
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Analysis of the capabilities of an information system for improving sleep quality based on biometric data analysis by M.S. Graf, A.V. Yakoniuk, D.V. Krant, I.I. Golovach

“…The system is able to function independently thanks to the use of machine learning algorithms, including LSTM for prediction, Kalman filter for data cleaning, Isolation Forest for anomaly detection, and K-means for clustering sleep patterns.…”
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Apple Trajectory Prediction in Orchards: A YOLOv8-EK-IPF Approach by Jinxing Niu, Zhengyi Liu, Shuo Wang, Jiaxi Huang, Junlong Zhao

“…The algorithm first employs spatial partitioning according to the cyclical motion patterns of apples to constrain the prediction results. …”
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A Multifrequency Brain Network-Based Deep Learning Framework for Motor Imagery Decoding by Juntao Xue, Feiyue Ren, Xinlin Sun, Miaomiao Yin, Jialing Wu, Chao Ma, Zhongke Gao

“…The filter bank common spatial pattern (FBCSP) algorithm filters the MI-based EEG signals in the spatial domain to extract features. …”
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Promotion or inhibition? Exploring the influence of the digital economy on urban-rural integration: A case study of yellow River basin by Mingxi Zhou, Fuyou Guo, Yongsheng Sun, Jiamin Ren, Xuebo Zhang

“…Using the Yellow River Basin as an empirical case study area, the projection pursuit model, simulated annealing algorithm and spatial Durbin model were employed to explore the impact of the digital economy on urban-rural integration in the Yellow River Basin from 2011 to 2021. …”
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Prediction Model of Household Carbon Emission in Old Residential Areas in Drought and Cold Regions Based on Gene Expression Programming by Shiao Chen, Yaohui Gao, Zhaonian Dai, Wen Ren

“…Focusing on 15 typical aging communities in Kundulun District, Baotou City, a 17-dimensional dataset encompassing building characteristics, demographic structure, and energy consumption patterns was collected through field surveys. Key influencing factors (e.g., electricity usage and heating energy consumption) were selected using Pearson correlation analysis and the Random Forest (RF) algorithm. …”
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Biosynthesis, applications, and mathematical modeling dynamics of lactic acid bacteria exopolysaccharides: A review by Ankit Barot, Kalyan Das, Yogesh Patel, et al.

“…White-box models, utilize comprehensive system knowledge, forecast performance, and optimize processes such as EPS biosynthesis while employing algorithms like fuzzy patterns, rule-based systems, and decision trees to increase productivity and identify bottlenecks. …”
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Machine Learning Techniques Applied to COVID-19 Prediction: A Systematic Literature Review by Yunyun Cheng, Rong Cheng, Ting Xu, Xiuhui Tan, Yanping Bai

“…Since the outbreak of COVID-19, there has been an influx of research on predictive modelling, with artificial intelligence (AI) techniques, particularly machine learning (ML) methods, becoming the dominant research direction due to their superior capability in processing multidimensional datasets and capturing complex nonlinear transmission patterns. …”
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Explainability of Network Intrusion Detection Using Transformers: A Packet-Level Approach by Pahavalan Rajkumardheivanayahi, Ryan Berry, Nicholas U. Costagliola, Lance Fiondella, Nathaniel D. Bastian, Gokhan Kul

“…Machine learning based NIDS models leverage algorithms that learn from historical network traffic data to identify patterns and anomalies to capture complex relationships. …”
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Human Clustering Based on Graph Embedding and Space Functions of Trajectory Stay Points on Campus by Ke Xie, Tao Wang, Pan Zhong, Zihao Zhao, Zixiang Wang

“…Available research on spatial clustering patterns of human activities has been investigated mainly based on similarities of locations and temporal attributes of spatial trajectories. …”
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Characteristics of pore-fracture structure and three-dimensional spatial distribution differences in deep and shallow coal reservoirs: A case study of Junggar Basin by WANG Pengxiang, ZHANG Zhou, YU Wanying, ZOU Qiang, YANG Zhengtao

“…A pore network model for the samples was established using the maximal sphere algorithm to analyze the distribution pattern, morphology, and three-dimensional structural development of the connected pores and fractures. …”
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Leveraging environmental microbial indicators in wastewater for data-driven disease diagnostics by Gayatri Gogoi, Gayatri Gogoi, Sarangthem Dinamani Singh, Sarangthem Dinamani Singh, Devpratim Koch, Devpratim Koch, Emon Kalyan, Rashmi Rani Boro, Aradhana Devi, Hridoy Jyoti Mahanta, Hridoy Jyoti Mahanta, Pankaj Bharali, Pankaj Bharali

“…Unsupervised learning algorithms, including K-means and K-medoid clustering, were employed to categorize the data into four distinct clusters, revealing patterns of viral positivity and environmental conditions.ResultsCluster analysis indicated that seasonal variations and water quality characteristics significantly influenced SARS-CoV-2 positivity rates. …”
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Clinical Utility of Bladder Cancer Biomarkers by Laura Maria Krabbe, Georgios Gakis, Yair Lotan

“…Intense research has resulted in the recent approval by the U. …”
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Influenza virus genotype to phenotype predictions through machine learning: a systematic review by Laura K. Borkenhagen, Martin W. Allen, Jonathan A. Runstadler

“…Machine learning techniques have demonstrated promise in addressing this critical need for other pathogens because the underlying algorithms are especially well equipped to uncover complex patterns in large datasets and produce generalizable predictions for new data. …”
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Using the proximal policy optimization and prospect theory to train a decision-making model for managing personal finances by Vladyslav Didkivskyi, Dmytro Antoniuk, Tetiana Vakaliuk, Yevhen Ohinskyi

“…A graphical analysis of the recommended allocation percentages revealed significant patterns influenced by the value function parameters of Prospect Theory. …”
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