Post-Processing Optimization of the Global 30 m Land Cover Dynamic Monitoring Product by Zhehua Li, Xiao Zhang, Wendi Liu, Tingting Zhao, Weitao Ai, Jinqing Wang, Liangyun Liu

“…Post-processing optimization refers to the refinement of land cover products by applying specific rules or algorithms to minimize erroneous changes in land cover types caused by classification uncertainty or interannual phenological variations. …”
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URGENT X-RAY DIAGNOSTICS OF INTRACRANIAL PYOINFLAMMATORY OTORHINOSINUSOGENIC COMPLICATIONS by I. S. Piskunov, Yu. A. Shcherbuk, A. A. Krivopalov, A. N. Rubin, I. E. Glaz’Ev, E. A. Nekhaeva

“…The authors presents a complex of symptoms and an algorithm of differentiated X-ray diagnostics of diseases of the ENT organs and the main nosological forms of pyoinflammatory diseases of arachnoid membrane and substances of the brain.…”
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A Probabilistic Method for Estimation of Bowel Wall Thickness in MR Colonography. by Thomas Hampshire, Alex Menys, Asif Jaffer, Gauraang Bhatnagar, Shonit Punwani, David Atkinson, Steve Halligan, David J Hawkes, Stuart A Taylor

“…We show that the variability of wall thickness measurement between the algorithm and observer measurements (0.25mm ± 0.81mm) has differences which are similar to observer variability (0.16mm ± 0.64mm).…”
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Comparison of Random Survival Forest Based‐Overall Survival With Deep Learning and Cox Proportional Hazard Models in HER‐2‐Positive HR‐Negative Breast Cancer by Wenqi Cai, Yan Qi, Linhui Zheng, Huachao Wu, Chunqian Yang, Runze Zhang, Chaoyan Wu, Haijun Yu

“…Predictive models were developed using five feature sets and three algorithms (Cox PH, RSF, DeepSurv), with feature selection optimized via Concordance index (C‐index). …”
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A comprehensive review of data analytics and storage methods in geothermal energy operations by Ali Basem, Ahmed Kateb Jumaah Al-Nussairi, Dana Mohammad Khidhir, Narinderjit Singh Sawaran Singh, Mohammadreza Baghoolizadeh, Mohammad Ali Fazilati, Soheil Salahshour, S. Mohammad Sajadi, Ali Mohammadi Hasanabad

“…The adaptability of BTES to different ground conditions and its small land footprint made it a spotlight for the researchers. …”
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Automatic magnetic resonance imaging series labelling for large repositories by Armando Gomis-Maya, Leonor Cerdá-Alberich, Diana Veiga-Canuto, Salvatore Claudio-Fanni, Amadeo Ten-Steve, Gloria Ribas-Despuig, Pedro José Mallol-Roselló, Joan Vila-Frances, Luis Marti-Bonmati

“…Moreover, the inference performance of the end system has been evaluated on 25,596 MR series as well as the final model outputs with an external evaluation set of 1286 MR series. …”
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Research on Traffic Accident Severity Level Prediction Model Based on Improved Machine Learning by Jiming Tang, Yao Huang, Dingli Liu, Liuyuan Xiong, Rongwei Bu

“…Decision tree, XGBoost, and random forest algorithms, respectively, were applied for the secondary prediction. …”
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Screening of potential markers for vitiligo based on bioinformatics and LASSO regression and prediction of Chinese medicine by Wei Liang, Minni Huang, Yue Sun, Shuyu Guan

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Spectral Fingerprinting of Tencha Processing: Optimising the Detection of Total Free Amino Acid Content in Processing Lines by Hyperspectral Analysis by Qinghai He, Yihang Guo, Xiaoli Li, Yong He, Zhi Lin, Hui Zeng

“…This study employs VNIR-HSI combined with machine learning algorithms to develop a model for visualizing the total free amino acid content in Tencha samples that have undergone different processing steps on the production line. …”
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A novel perspective on survival prediction for AML patients: Integration of machine learning in SEER database applications by Zheng-yi Jia, Maierbiya Abulimiti, Yun Wu, Li-na Ma, Xiao-yu Li, Jie Wang

“…Finally, we used 11 machine learning algorithms to predict the survival rate of AML patients at 1, 2, and 3 years, respectively. …”
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Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer by Erha Munai, Siwei Zeng, Ze Yuan, Dingyi Yang, Yong Jiang, Qiang Wang, Yongzhong Wu, Yunyun Zhang, Dan Tao

“…Patients diagnosed with ES-SCLC between 2010 and 2018 were screened from the Surveillance, Epidemiology, and End Results (SEER) database. Four different machine learning (ML) algorithms were used to create prediction models for BMs in ES-SCLC patients. …”
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Optimizing photocatalytic dye degradation: A machine learning and metaheuristic approach for predicting methylene blue in contaminated water by Yunus Ahmed, Keya Rani Dutta, Sharmin Nahar Chowdhury Nepu, Meherunnesa Prima, Hamad AlMohamadi, Parul Akhtar

“…Ten different machine learning models, including AdaBoost, Bagging, CatBoost, Decision Tree, Extra Trees, Gradient Boosting, HistGradientBoosting, LightGBM, Random Forest, and XGBoost, were evaluated using CuWO₄@TiO₂ as a photocatalyst. …”
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Artificial Intelligence in Forensic Expertology by E. V. Chesnokova, A. I. Usov, G. G. Omel’yanyuk, M. V. Nikulina

“…Process cycle is a set of sequential actions at different levels: initiation of AI technology, evaluation (suitability) of its results at the first level, adjustment and implementation of the updated version of AI technology, assessment of the next level, etc. …”
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Optimizing AI Transformer Models for <italic>CO</italic>&#x2082; Emission Prediction in Self-Driving Vehicles With Mobile/Multi-Access Edge Computing Support by Javier Saez-Perez, Pablo Benlloch-Caballero, David Tena-Gago, Jose Garcia-Rodriguez, Jose Maria Alcaraz Calero, Qi Wang

“…With the increasing prominence of self-driving vehicles, there has been a pressing need to accurately estimate their carbon dioxide (CO2) emissions and evaluate their environmental sustainability. This paper has introduced a novel approach that leverages Artificial Intelligence (AI) transformer architectures to predict CO2 emissions in Society of Automotive Engineers (SAE) Level 2 self-driving cars, surpassing the performance of previous algorithms. …”
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Sex-Specific Ensemble Models for Type 2 Diabetes Classification in the Mexican Population by Mendoza-Mendoza MM, Acosta-Jiménez S, Galván-Tejada CE, Maeda-Gutiérrez V, Celaya-Padilla JM, Galván-Tejada JI, Cruz M

“…Data are split by sex, and feature selection is performed using GALGO, a genetic algorithm-based tool. Classification models including Random Forest, K-Nearest Neighbor, Support Vector Machine, and Logistic Regression are trained and evaluated. …”
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Person centered care for primary ovarian insufficiency: developing and testing patient-facing materials co-created with patients by Elizabeth S. Blocker, Isabella R. McDonald, Elizabeth A. Weyman, Dana L. Jarvis, Joni Bryce, Corrine K. Welt, Corrine K. Welt, Andrew A. Dwyer, Andrew A. Dwyer

“…Validated algorithms (n = 8) were employed to determine PEM readability prior to evaluation. …”
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Privacy-Preserving Federated Learning for Space–Air–Ground Integrated Networks: A Bi-Level Reinforcement Learning and Adaptive Transfer Learning Optimization Framework by Ling Li, Lidong Zhu, Weibang Li

“…This paper proposes a Privacy-Preserving Federated Learning framework for SAGIN (PPFL-SAGIN), which for the first time integrates differential privacy, adaptive transfer learning, and bi-level reinforcement learning to systematically address data heterogeneity, device dynamics, and privacy leakage in SAGINs. …”
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A Study on Staging Cystic Echinococcosis Using Machine Learning Methods by Tuvshinsaikhan Tegshee, Temuulen Dorjsuren, Sungju Lee, Dolgorsuren Batjargal

“…This study explores the development of an advanced system that leverages artificial intelligence (AI) and machine learning (ML) techniques to classify CE cysts into stages using various imaging modalities, including computed tomography (CT), ultrasound (US), and magnetic resonance imaging (MRI). A total of ten ML algorithms were evaluated across these datasets, using performance metrics such as accuracy, precision, recall (sensitivity), specificity, and F1 score. …”
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Analytical Insight into Some Fractional Nonlinear Dynamical Systems Involving the Caputo Fractional Derivative Operator by Mashael M. AlBaidani

“…The developed computational techniques yield numerical and graphical output, which are compared to analytic results to verify the solution convergence. The computational algorithms have proven their high accuracy, flexibility, effectiveness, and simplicity in evaluating fractional-order mathematical models.…”
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Tissue Is the Issue: A Systematic Review of Methods for the Determination of Infarct Volume in Acute Ischaemic Stroke by Fatimah Al Ahmed, Patrick Kennelly, Darragh Herlihy, Jorin Bejleri, David J. Williams, John J. Thornton, Shona Pfeiffer

“…Semi-automated and automated approaches with user refinement showed excellent inter-rater and intra-rater correlation. However, differences in operating algorithms and lack of standardisation of image acquisition parameters, quality, and format may impact performance and reproducibility. …”
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