Identification of potential diagnostic markers and molecular mechanisms of asthma and ulcerative colitis based on bioinformatics and machine learning by Chenxuyu Zhang, Chenxuyu Zhang, Zheng Luo, Liang Ji

“…Gene Set Enrichment Analysis (GSEA) explored pathway alterations, while immune infiltration patterns were analyzed using the CIBERSORT algorithm. Molecular docking (MD) was performed to predict therapeutic compounds, followed by molecular dynamics simulations on the top-ranked docked complex to assess its binding stability.ResultsA total of 41 shared genes were identified, linked to inflammatory and immune pathways, including TNF, IL-17, and chemokine signaling. …”
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Convolutional neural network for maxillary sinus segmentation based on the U-Net architecture at different planes in the Chinese population: a semantic segmentation study by Jiayi Chen

“…The best model was retained for predicting MS in the test set and calculating the model parameters. …”
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Mathematical solutions for coupled nonlinear equations based on bioconvection in MHD Casson nanofluid flow by Khalil Ur Rehman, Nosheen Fatima, Wasfi Shatanawi, Nabeela Kousar

“…ODEs were then numerically solved in MATLAB software using the built-in solver bvp4c algorithm. We established an artificial neural network (ANN) model, incorporating Tan-Sig and Purelin transfer functions, to enhance the accuracy of predicting skin friction coefficient (SFC) values along the surface. …”
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Analysis and Application of Grey-Markov Chain Model in Tax Forecasting by Huidi Zhang, Yimao Chen

“…The key to correct tax forecasting is the choice of forecasting algorithm. Traditional tax forecasting methods, such as factor scoring method, factor regression method, and system adjustment method, have a certain guiding role in actual work, but there are still many shortcomings, such as the limitation from the distribution and size of sample data and difficulty of grasping the nonlinear phenomena in economic system. …”
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Comprehensive analysis of IRF8-related genes and immune characteristics in lupus nephritis by Zhibin Yu, Chenghui Zheng, Yilun Wang

“…To bridge our findings with potential therapeutic implications, we used the drug-gene interaction database to predict drugs targeting the identified genes.ResultsTwenty co-differentially expressed genes (DEGs) were identified, with IRF8 exhibiting significant expression differences and potential as a biomarker. …”
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Exploration of the Prognostic Markers of Multiple Myeloma Based on Cuproptosis‐Related Genes by Xiao‐Han Gao, Jun Yuan, Xiao‐Xia Zhang, Rui‐Cang Wang, Jie Yang, Yan Li, Jie Li

“…Conclusion As a result of this investigation, a set of six biomarkers associated with cuproptosis (PARP1, EDEM3, SEC23A, RSL24D1, TTC37, and SRP72) were screened to provide a basis for predicting the prognosis of MM.…”
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Graph-Based Radiomics Feature Extraction From 2D Retina Images by Ofelio Jorreia, Nuno Goncalves, Rui Cortesao

“…The trained model achieved an accuracy of 94.95% in correctly identifying bifurcation points. Based on predicted bifurcation points and blood vessel segments, we use the Graph-Based Radiomics Feature Extraction Algorithm (Graph-BRFExtract) to extract the adjacency matrix. …”
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Radar versus optical: The impact of cloud cover when mapping seasonal surface water for health applications in monsoon-affected India. by Gowri Uday, Bethan V Purse, Douglas I Kelley, Abi Vanak, Abhishek Samrat, Anusha Chaudhary, Mujeeb Rahman, France F Gerard

“…Backscatter thresholds were identified manually, and our Bayesian algorithm found these thresholds were very likely (>97%). …”
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Application of Internet marketing tools for management decision-making by logistics enterprises by O.A., T.O., O.P., H.Yu.

“…The direct influence of the size of the advertising budget on the predicted indicators of targeted advertising has been proven. …”
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GEOECOLOGICAL DIAGNOSTICS OF THE REGIONS IN THE CENTRALBLACK SOIL REGION by S. A. Kurolap, N. V. Yakovenko, V. I. Fedotov, V. B. Mikhno, L. N. Kostyleva

“…The authors propose an algorithm to perform geoecological diagnostics of the large region. …”
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Forecasting water quality indices using generalized ridge model, regularized weighted kernel ridge model, and optimized multivariate variational mode decomposition by Marjan Kordani, Mohsen Bagheritabar, Iman Ahmadianfar, Arvin Samadi-Koucheksaraee

“…For this reason, the suggested OMVMD-GRKR model serves as a valuable framework for predicting IWQI parameters.…”
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The Application of Artificial Digital Models in X-Ray Computed Tomography (CT) of the Core in Solving the Problem of Binarization of the Void Space of Reservoir Rocks by O. A. Melkishev, Y. V. Savitsky, S. V. Galkin

“…The use of the proposed model for predicting boundary values on obtained tomograms demonstrated a high degree of consistency with actual data.…”
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Snow Distribution Patterns Revisited: A Physics‐Based and Machine Learning Hybrid Approach to Snow Distribution Mapping in the Sub‐Arctic by R. L. Crumley, C. L. Bachand, K. E. Bennett

“…Recent advances in snow hydrology and machine learning (ML) have increased our ability to predict snowpack distribution using in‐situ observations, remote sensing data sets, and simple landscape characteristics that can be easily obtained for most environments. …”
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Statistics and behavior of clinically significant extra-pulmonary vein atrial fibrillation sources: machine-learning-enhanced electrographic flow mapping in persistent atrial fibri... by Peter Ruppersberg, Steven Castellano, Philip Haeusser, Kostiantyn Ahapov, Melissa H. Kong, Stefan G. Spitzer, Stefan G. Spitzer, Georg Nölker, Andreas Rillig, Tamas Szili-Torok

“…Our machine learning approach established an activity threshold, above which divergent wavefront patterns—termed “significant sources”—predicted AF recurrence. This threshold was validated in 85 prospective patients from the published FLOW-AF trial. …”
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Penerapan Metode K-Medoids untuk Pengelompokan Mahasiswa Berpotensi Drop Out by Syamsul Bahri, Dwi Marisa Midyanti

“…Dropout students can be predicted through several processes of obtaining patterns or knowledge from data sets called data mining. …”
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A large-scale ENIGMA multisite replication study of brain age in depression by Laura K.M. Han, Richard Dinga, Ramona Leenings, Tim Hahn, James H. Cole, Lyubomir I. Aftanas, Alyssa R. Amod, Bianca Besteher, Romain Colle, Emmanuelle Corruble, Baptiste Couvy-Duchesne, Konstantin V. Danilenko, Paola Fuentes-Claramonte, Ali Saffet Gonul, Ian H. Gotlib, Roberto Goya-Maldonado, Nynke A. Groenewold, Paul Hamilton, Naho Ichikawa, Jonathan C. Ipser, Eri Itai, Sheri-Michelle Koopowitz, Meng Li, Go Okada, Yasumasa Okamoto, Olga S. Churikova, Evgeny A. Osipov, Brenda W.J.H. Penninx, Edith Pomarol-Clotet, Elena Rodríguez-Cano, Matthew D. Sacchet, Hotaka Shinzato, Kang Sim, Dan J. Stein, Aslihan Uyar-Demir, Dick J. Veltman, Lianne Schmaal

“…Results: Our ENIGMA MDD brain age model generalized reasonably well to controls from the new cohorts (predicted age vs. age: r = 0.73, R2 = 0.47, MAE = 7.50 years), although the performance varied from cohort to cohort. …”
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In silico assessment of biocompatibility and toxicity: molecular docking and dynamics simulation of PMMA-based dental materials for interim prosthetic restorations by Ravinder S. Saini, Rayan Ibrahim H. Binduhayyim, Vishwanath Gurumurthy, Abdulkhaliq Ali F. Alshadidi, Shashit Shetty Bavabeedu, Rajesh Vyas, Doni Dermawan, Punnoth Poonkuzhi Naseef, Seyed Ali Mosaddad, Artak Heboyan

“…Methodology: Molecular docking was employed to predict the binding affinities, energetics, and steric features of MMA and PMMA with selected receptors involved in bone metabolism and tissue development, including RANKL, Fibronectin, BMP9, NOTCH2, and other related receptors. …”
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Molecular profiles of tumor contrast enhancement: A radiogenomic analysis in anaplastic gliomas by Xing Liu, Yiming Li, Zhiyan Sun, Shaowu Li, Kai Wang, Xing Fan, Yuqing Liu, Lei Wang, Yinyan Wang, Tao Jiang

“…Our gene signature helps interpret the occurrence of radiological traits and predict clinical outcomes. Additionally, we found nine prognostic quantitative radiomic features of CE and investigated the underlying biological processes of them.…”
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Multi-modality radiomics diagnosis of breast cancer based on MRI, ultrasound and mammography by Jiao Wu, YongXin Li, Wanqing Gong, Qian Li, Xue Han, Tingting Zhang

“…Conclusions The multi-modality radiomics model based on MRI, ultrasound, and mammography can predict benign and malignant breast lesions.…”
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A Meta-Learning-Based Ensemble Model for Explainable Alzheimer’s Disease Diagnosis by Fatima Hasan Al-bakri, Wan Mohd Yaakob Wan Bejuri, Mohamed Nasser Al-Andoli, Raja Rina Raja Ikram, Hui Min Khor, Zulkifli Tahir, The Alzheimer’s Disease Neuroimaging Initiative

“…The findings demonstrated significant progress in diagnostic transparency, as the algorithm consistently linked predictions to observed structural changes in the dilated lateral ventricles of the brain, which serve as a clinically reliable biomarker for AD and can be easily verified by medical professionals. …”
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