Cervical cancer demystified: exploring epidemiology, risk factors, screening, treatment modalities, preventive measures, and the role of artificial intelligence by N. Mohammad, M. Khan, M. Maqsood, A. H. K. Naseeb

“…AI-driven technologies, including deep learning algorithms and machine learning models, are emerging as valuable tools in cervical cancer detection, risk assessment, and treatment planning. …”
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Heterogeneous Graph Attention Networks for Scheduling in Cloud Manufacturing and Logistics by Dmitrii Fomin, Ilya Makarov, Mariia Voronina, Anna Strimovskaya, Vitaliy Pozdnyakov

“…Our model minimizes both manufacturing and logistics costs, achieving significant performance improvements over greedy algorithms and comparable results to strong genetic algorithms in large-scale scenarios with up to 20 locations. …”
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Multi-omics derivation of a core gene signature for predicting therapeutic response and characterizing immune dysregulation in inflammatory bowel disease by Mingming Wang, Liping Liang, Zibo Tang, Jimin Han, Lele Wu, Le Liu, Le Liu, Ye Chen, Ye Chen

“…Validation employed ten algorithms and nomogram construction. Immune infiltration (CIBERSORT/ssGSEA), single-cell RNA sequencing, and DSS-colitis models characterized immune dynamics, cellular specificity, and therapeutic response modulation.ResultsWe identified 536 differentially expressed genes significantly enriched in IL-17 signaling, TNF signaling, and cytokine-cytokine receptor interactions. …”
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Contributions to the Development of Tetrahedral Mobile Robots with Omnidirectional Locomotion Units by Anca-Corina Simerean, Mihai Olimpiu Tătar

“…The second prototype is presented as an advanced and improved version of the first model, integrating significant modifications in both the structural design and the robot’s functionality. …”
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Screening and Risk Analysis of Atrial Fibrillation After Radiotherapy for Breast Cancer: Protocol for the Cross-Sectional Cohort Study “Watch Your Heart (WATCH)” by Laura Saint-Lary, Baptiste Pinel, Loic Panh, Gaelle Jimenez, Julien Geffrelot, Youlia Kirova, Jeremy Camilleri, David Broggio, Marie-Odile Bernier, Corinne Mandin, Christelle Levy, Serge Boveda, Juliette Thariat, Sophie Jacob

“…Cross-sectional screening for AF at the time of the scheduled 5-year post-RT visit will be conducted by recording data from a Withings ScanWatch smartwatch for 1 month, confirmed by an electrocardiogram (ECG), and validated by a physician. …”
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Designing CITOBOT: A portable device for cervical cancer screening using human-centered design, smart prototyping, and artificial intelligence by Marcela Arrivillaga, Paula C. Bermúdez, Juan Pablo García-Cifuentes, Hernán Darío Vargas-Cardona, Daniela Neira, Maria del Mar Torres, Mérida Rodríguez-López, Daniela Morales, Bleider Arizala

“…Additionally, we developed AI algorithms using the Inception V3 network, optimized with Transfer Learning and Fine Tuning, for cervical image classification and offline-operating software that guides the physician through the examination and provides a risk assessment for cervical cancer. …”
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Comparative Analysis of Facial Expression Recognition Methods by Denys - Florin COT

“…The integration of such solutions can contribute to the development of decision support systems in psychiatry, optimizing therapeutic strategies, and improving the quality of care for patients with neuropsychological conditions. …”
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Comparison of Machine Learning Methods for Predicting Electrical Energy Consumption by Retno Wahyusari, Sunardi Sunardi, Abdul Fadlil

“…Data pre-processing, specifically min-max normalization, is crucial for improving the accuracy of distance-based algorithms like KNN. …”
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Development and Training of a Neural Network Filter for Satellite Images Processing by N. Andriyanov, A. Kim

“…As part of the study, the architecture of the autoencoder was developed, optimal hyperparameters were selected and the resulting neural network model was trained. …”
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Postmarketing safety evaluation of pemetrexed using FAERS and JADER databases by Luo Lv, Xiangyang Wu, Yubo Ren, Yuli Guo, Haixiong Wang, Xiaofang Li

“…Continuous pharmacovigilance is essential to optimize its clinical use and improve patient safety.…”
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Pertinence of contact duration as edge feature for epidemic spread analysis by Ramya D. Shetty, Shrutilipi Bhattacharjee

“…In this study, we mainly aim to generate weighted networks to model the pathogen spread by optimal calculation of the edge weight in terms of contact duration (time spent) between individual contacts. …”
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Know your competitor! Analyzing and predicting the location of competing stores: The case study of Valora at Swiss railway stations by Thomas Wieland

“…Machine learning algorithms are used to check and optimize the predictive ability of the models. …”
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What factors enhance students' achievement? A machine learning and interpretable methods approach. by Hui Mao, Ribesh Khanal, ChengZhang Qu, HuaFeng Kong, TingYao Jiang

“…This study addresses these limitations by employing an ensemble of five machine learning algorithms (SVM, DT, ANN, RF, and XGBoost) to model multivariate relationships between four behavioral and six instructional predictors, using final exam performance as our outcome variable. …”
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Advancing Stability in Robot Manipulators: A Review of Recent Progress and Parameters by Shabnom Mustary, Mohammod Abul Kashem, Jannatul Mawya Sony, Nayem Hossain, Mohammad Asaduzzaman Chowdhury

“…Advancements comprise advanced control algorithms, sensor technology, and new mechanical schemas (rigid, flexible and hybrid). …”
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Large-scale S-box design and analysis of SPS structure by Lan ZHANG, Liangsheng HE, Bin YU

“…A class of optimal linear transformation P over a finite field<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> <msup> <mrow> <mrow><mo>(</mo> <mrow> <msubsup> <mi>F</mi> <mn>2</mn> <mi>m</mi> </msubsup> </mrow> <mo>)</mo></mrow></mrow> <mn>4</mn> </msup> </mrow></math></inline-formula> was constructed based on cyclic shift and XOR operation.Using the idea of inverse proof of input-output relation of linear transformation for reference, a proof method was put forward that transformed the objective problem of optimal linear transformation into several theorems of progressive relation, which not only solved the proof of that kind of optimal linear transformation, but also was suitable for the proof of any linear transformation.By means of small-scale S-box and optimal cyclic shift-XOR linear transformation P, a large-scale S-box model with 2-round SPS structure was established, and a series of lightweight large-scale S-boxes with good cryptographic properties were designed.Only three kind of basic operations such as look-up table, cyclic shift and XOR were used in the proposed design scheme, which improved the linearity and difference uniformity of large-scale S-boxes.Theoretical proof and case analysis show that, compared with the existing large-scale S-box construction methods, the proposed large-scale S-box design scheme has lower computational cost and better cryptographic properties such as difference and linearity, which is suitable for the design of nonlinear permutation coding of lightweight cryptographic algorithms.…”
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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction by Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu

“…Given the pivotal role of ventilators, accurately predicting extubation outcomes is essential to optimize patient care. This study presents an edge computing-based framework that incorporates machine learning algorithms to predict ventilator extubation success using real-time data collected directly from ventilators. …”
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AEM-D3QN: A Graph-Based Deep Reinforcement Learning Framework for Dynamic Earth Observation Satellite Mission Planning by Shuo Li, Gang Wang, Jinyong Chen

“…These features are then encoded into a reinforcement learning model that dynamically optimizes scheduling policies under multiple resource constraints. …”
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Fully automated multicolour structured illumination module for super-resolution microscopy with two excitation colours by Haoran Wang, Peter T. Brown, Jessica Ullom, Douglas P. Shepherd, Rainer Heintzmann, Benedict Diederich

“…To optimize DMD diffraction, we developed a model for tilt and roll pixel configurations, enabling use with various low-cost projectors in SIM setups. …”
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Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis by ShinYe Kim, Winson Fu Zun Yang, Zishan Jiwani, Emily Hamm, Shreya Singh

“…MethodsWe collected 1,438,644 pain-related tweets posted between January and December 2021 using tweepy and snscrape. …”
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Tumor tissue-of-origin classification using miRNA-mRNA-lncRNA interaction networks and machine learning methods by Ankita Lawarde, Ankita Lawarde, Masuma Khatun, Prakash Lingasamy, Prakash Lingasamy, Andres Salumets, Andres Salumets, Andres Salumets, Vijayachitra Modhukur, Vijayachitra Modhukur

“…Using transcriptomic profiles from 14 cancer types in The Cancer Genome Atlas (TCGA), we constructed co-expression networks and applied multiple feature selection techniques including recursive feature elimination (RFE), random forest (RF), Boruta, and linear discriminant analysis (LDA) to identify a minimal yet informative subset of miRNA features. Ensemble ML algorithms were trained and validated with stratified five-fold cross-validation for robust performance assessment across class distributions.ResultsOur models achieved an overall 99% classification accuracy, distinguishing 14 cancer types with high robustness and generalizability. …”
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