Predicting sleep quality among college students during COVID-19 lockdown using a LASSO-based neural network model by Lufeng Chen, Qingquan Chen, Zhimin Huang, Ling Yao, Jiajing Zhuang, Haibin Lu, Yifu Zeng, Jimin Fan, Ailing Song, Yixiang Zhang

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Feature-Driven EnsembleX: An Advanced Ensemble Framework for Enhanced MRI Abdomen Image Classification Using Feature Refinement and Boosting Techniques by Snehal V. Laddha, Rohini S. Ochawar

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Socioeconomic status and lifestyle as factors of multimorbidity among older adults in China: results from the China Health and Retirement Longitudinal Survey by Wei Gong, Wei Gong, Wei Gong, Xiaoxiao Hu, Huimin Cui, Huimin Cui, Yuxin Zhao, Yuxin Zhao, Hong Lin, Hong Lin, Hong Lin, Peng Sun, Peng Sun, Jianjun Yang, Jianjun Yang

“…Subgroup analyses showed variated associations by age and sex, with psychological and geographic factors playing a larger role among those aged ≥80.ConclusionThis study demonstrated the feasibility and interpretability of using machine learning to model complex risk patterns of multimorbidity. …”
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Integrative analysis of seed morphology, geographic origin, and genetic structure in Medicago with implications for breeding and conservation by Seunghyun Lim, Sunchung Park, Insuck Baek, Jacob Botkin, Jae Hee Jang, Seok Min Hong, Brian M. Irish, Moon S. Kim, Lyndel W. Meinhardt, Shaun J. Curtin, Ezekiel Ahn

“…Conclusions Our integrated analysis of phenotypic, genetic, and geographic data, coupled with a machine learning-based GWAS approach, provides valuable insights into the diverse patterns within Medicago spp. …”
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Prediction of Key Quality Parameters in Hot Air-Dried Jujubes Based on Hyperspectral Imaging by Quancheng Liu, Chunzhan Yu, Yuxuan Ma, Hongwei Zhang, Lei Yan, Shuxiang Fan

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Comprehensive Analysis of Programmed Cell Death-Related Genes in Diagnosis and Synovitis During Osteoarthritis Development: Based on Bulk and Single-Cell RNA Sequencing Data by Zhou J, Jiao S, Huang J, Dai T, Xu Y, Xia D, Feng Z, Chen J, Li Z, Hu L, Meng Q

“…Unsupervised consensus clustering analysis and weighted correlation network analysis (WGCNA) were employed to identify differential clustering patterns of PCD-related genes in OA patients. The molecular characteristics of Hub PCD-DEGs, their role in synovial immune inflammation, and their association with the immune microenvironment were investigated through functional enrichment analysis and ssGSEA immune infiltration analysis. …”
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A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…Advanced predictive models like logistic Regression and XGBoost analyze critical variables, identify patterns, and perform predictive analysis. These models can identify potential impactions, assess impaction type, and develop treatment plans. …”
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Exploring the predictive value of structural covariance networks for the diagnosis of schizophrenia by Clara S. Vetter, Clara S. Vetter, Clara S. Vetter, Annika Bender, Dominic B. Dwyer, Dominic B. Dwyer, Dominic B. Dwyer, Max Montembeault, Anne Ruef, Katharine Chisholm, Lana Kambeitz-Ilankovic, Linda A. Antonucci, Stephan Ruhrmann, Joseph Kambeitz, Marlene Rosen, Theresa Lichtenstein, Anita Riecher-Rössler, Rachel Upthegrove, Raimo K. R. Salokangas, Jarmo Hietala, Christos Pantelis, Christos Pantelis, Rebekka Lencer, Rebekka Lencer, Eva Meisenzahl, Stephen J. Wood, Stephen J. Wood, Paolo Brambilla, Paolo Brambilla, Stefan Borgwardt, Peter Falkai, Peter Falkai, Alessandro Bertolino, Nikolaos Koutsouleris, Nikolaos Koutsouleris, Nikolaos Koutsouleris, PRONIA Consortium

“…Risk estimates derived from KLS-SCNs and regional GMV, but not REF-SCNs, could be predicted from clinical variables, especially driven by body mass index (BMI) and affect-related negative symptoms.DiscussionThese patterns of results show that different SCN computation approaches capture different aspects of the disease. …”
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Urban-rural inequality in soil heavy metal health risks: Insights from Baoding, China by Lingzhi Luo, Liang Wang, You Li, Hongying Cao, Yanling Guo, Xiaoyong Liao

“…This integrated approach advances scientific understanding of how urbanization shapes spatial health risk patterns and provides actionable insights for targeted environmental management to protect vulnerable communities, inform mitigation strategies, and identify priority intervention areas.…”
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Analysis of fault detection and defect categorization in photovoltaic inverters for enhanced reliability and efficiency in large-scale solar energy systems by Malik Stephanie, Daßler David, Patel Dharm, Klute Carola, Klengel Robert, Dietrich Andreas, Kaufmann Kai, Hennig Carsten, Wehnert Danny, Ebert Matthias

“…A root cause analysis identified the failure pattern through material diagnostics of several power modules from inverters previously installed in the field. …”
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The utility of combining deep learning with metabarcoding to model biodiversity dynamics at a national scale by Adrian Baggström, Robert Goodsell, Laura van Dijk, Ela Iwaszkiewicz-Eggebrecht, Andreia Miraldo, Ayco J.M. Tack, Tobias Andermann

“…By combining detailed biodiversity surveys, geospatial data, and machine learning, we can model biodiversity with the aim of gaining insights into how these complex patterns behave. …”
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Fetal health classification with predictive algorithm by using Ensemble Model by Devi V. Sowmya, Kancharakuntla Manoj Reddy, Paleti Goutam Nayudu, Madhunala Akash

“…Cardiotocography (CTG) is a widely used technique that monitors fetal heart rate (FHR) patterns and uterine contractions, providing critical insights into fetal health. …”
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Citrus quality grading based on statistical complexity measurement and multifractal spectrum method by Cao Leping, Wen Zhiyuan

“…It can also make huge economic and social benefits and increase farmers income and agricultural productivity so as to promote the sustained and healthy development of the citrus industry.For the purpose of precise measurement of citrus quality grading, the complexity measurement of Bingtang orange defective fruit damaged by diseases and insect pest patterns were studied by machine recognition, along with the navel orange fruit perimeter-area fractal dimension and the shape, color grading and sugar acid nondestructive detection of section tone unit coordinates multifractal spectrum height and width.Physiological boron deficiency, Eriophyes oleivorus and rind oil spotting disease were very common in Bingtang orange fruits. …”
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AI-driven precision diagnosis and treatment in Parkinson’s disease: a comprehensive review and experimental analysis by Bhekisipho Twala

“…Additionally, we developed and tested a hybrid machine learning model combining deep learning, computer vision, and natural language processing techniques for PD assessment using motor symptom analysis, voice pattern recognition, and gait analysis.ResultsThe systematic review identified 127 relevant studies demonstrating significant advances in AI-driven PD diagnosis, with accuracy rates ranging from 78 to 96%. …”
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Automated inflammatory bowel disease detection using wearable bowel sound event spotting by Annalisa Baronetto, Annalisa Baronetto, Sarah Fischer, Sarah Fischer, Markus F. Neurath, Markus F. Neurath, Oliver Amft, Oliver Amft

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Unmasking Nuances Affecting Loneliness: Using Digital Behavioural Markers to Understand Social and Emotional Loneliness in College Students by Malik Muhammad Qirtas, Evi Zafeiridi, Eleanor Bantry White, Dirk Pesch

“…Our objectives were to (1) identify behavioural patterns linked to social and emotional loneliness, (2) evaluate the predictive power of these patterns for classifying loneliness types, and (3) determine the most significant digital markers used by machine learning models in loneliness prediction. …”
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A study on the correlation between MBTI dimensions and driving behavior characteristics by Liwei Bai, Tao Wang, Jianyao Tu, Bozhezi Peng, Zhuoyu Wang

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A deep fusion‐based vision transformer for breast cancer classification by Ahsan Fiaz, Basit Raza, Muhammad Faheem, Aadil Raza

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RAILWAY VEHICLES PANTOGRAPH FAULT DIAGNOSIS BASED ON VARIATIONAL MODE DECOMPOSITION DISPERSION ENTROPY AND SVM by PAN Ning

“…Finally, SVM was used as pattern recgnition method to identified the fault features and the diagnosis results are obtained. …”
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On the use of kolmogorov–arnold networks for adapting wind numerical weather forecasts with explainability and interpretability: application to madeira international airport by Décio Alves, Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias

“…A key outcome of this study comes from the model’s ability to generate mathematical formulas that provide insights into the physical and mathematical dynamics influencing local wind patterns and improve the transparency, explainability, and interpretability of the employed machine learning models for atmosphere modeling.…”
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