Machine-Learning-Driven Approaches for Assessment, Delegation, and Optimization of Multi-Floor Building by Abtin Baghdadi, Harald Kloft

“…Extensive parametric studies reveal the dominant impact of core wall dimensions and floor number on structural efficiency, while the application of stiffness reduction factors (e.g., <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>P</mi><mn>11</mn></msub></semantics></math></inline-formula>) proves effective in reducing material without compromising performance. …”
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Machine learning based identification of suicidal ideation using non-suicidal predictors in a university mental health clinic by Muhammed Ballı, Asli Ercan Dogan, Sevin Hun Senol, Hale Yapici Eser

“…Data from 924 university students seeking mental health services were analyzed using seven machine learning algorithms. Suicidal ideation was assessed through the 9th item of the Patient Health Questionnaire-9. …”
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Early detection of woody plant encroachment in Canadian prairies using UAV imagery and transformer-based deep learning by Yihan Pu, Xiaojing Lu, Irini Soubry, Xulin Guo

“…Spatial resolution degradation (from 0.73 cm to 3 cm) reduced detection accuracy for small shrub patches (diameters ∼10–20 cm), while showing minimal impact on larger patches (diameters >1 m). …”
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A Hybrid Artificial Intelligence Approach for Down Syndrome Risk Prediction in First Trimester Screening by Emre Yalçın, Serpil Aslan, Mesut Toğaçar, Süleyman Cansun Demir

“…The final features are classified using machine learning algorithms, including Bagged Trees and Naive Bayes. …”
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Mathematical model for prediction of Tuberculosis in Nigeria using hybrid fractional differential equations and artificial neural network methods by Samson Linus Manu, Shikaa Samuel, Taparki Richard, Eshi Priebe Dovi

“…Training of the NN involves minimizing a loss function combining data fit and system constraints, optimized using the Adam and L-BFGS algorithms, achieving a high degree of accuracy with an MSE of 6.005×10−6. …”
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Clinical applications of photon-counting CT in neuroimaging by LÜ Haiying, LU Yong, HE Naying

“…Photon-counting computed tomography (PCCT) is a next-generation CT imaging technology that markedly improves image quality while reducing radiation dose and image noise through single-photon detection and energy discrimination by photon detectors. …”
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Grey Wolf Optimization- and Particle Swarm Optimization-Based PD/I Controllers and DC/DC Buck Converters Designed for PEM Fuel Cell-Powered Quadrotor by Habibe Gursoy Demir

“…Both optimizers work together in the system and try to minimize tracking errors while also minimizing power consumption by using suitable objective functions. …”
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Dual-hybrid intrusion detection system to detect False Data Injection in smart grids. by Saad Hammood Mohammed, Mandeep S Jit Singh, Abdulmajeed Al-Jumaily, Mohammad Tariqul Islam, Md Shabiul Islam, Abdulmajeed M Alenezi, Mohamed S Soliman

“…Recall is enhanced by capturing critical features relevant to all attack types, while precision is improved by reducing false positives, leading to fewer unnecessary interventions. …”
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A Machine Learning Based Framework for a Stage-Wise Classification of Date Palm White Scale Disease by Abdelaaziz Hessane, Ahmed El Youssefi, Yousef Farhaoui, Badraddine Aghoutane, Fatima Amounas

“…To classify the WSD into its four classes (healthy, low infestation degree, medium infestation degree, and high infestation degree), two types of ML algorithms were tested; classical machine learning methods, namely, support vector machine (SVM) and k-nearest neighbors (KNN), and ensemble learning methods such as random forest (RF) and light gradient boosting machine (LightGBM). …”
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3D anatomical digital twins: New generation virtual models to navigate robotic partial nephrectomy by Daniele Amparore, Alberto Piana, Federico Piramide, Sabrina De Cillis, Enrico Checcucci, Cristian Fiori, Francesco Porpiglia

“…Textures are created from intraoperative robotic surgery images using machine learning algorithms. The result is a 3D model ‐ digital twin that replicates the organ's shape and appearance. …”
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Machine Learning-Based Prediction of Postoperative Deep Vein Thrombosis Following Tibial Fracture Surgery by Humam Baki, İsmail Bülent Özçelik

“…The top-performing model (random forest with RFE) attained an AUC of ~0.99, while several others (including LightGBM and SVM-based models) also reached AUC values in the 0.97–0.99 range. …”
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Artificial Intelligence-Based Prediction of Bloodstream Infections Using Standard Hematological and Biochemical Markers by Ferhat DEMİRCİ, Murat AKŞİT, Aylin DEMİRCİ

“…SHAP analysis revealed that age and PCT were the most influential features with both statistical and clinical relevance. Basophil count, while ranked highest by SHAP, showed low sensitivity, highlighting the difference between algorithmic weight and bedside utility. …”
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Identification of glucocorticoid-related genes in systemic lupus erythematosus using bioinformatics analysis and machine learning. by Yinghao Ren, Weiqiang Chen, Yuhao Lin, Zeyu Wang, Weiliang Wang

“…Among these, 1,458 genes were upregulated, while 1,223 were downregulated in cluster_1. GSVA showed significant changes in the pathways associated with cluster_1. …”
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Sensor‐Guided Smart Irrigation for Tomato Production: Comparing Low and Optimum Soil Moisture in Greenhouse Environments by Ibrahim Dirlik, Ferhat Uğurlar, Cengiz Kaya

“…Treatment 1 (T1) involved low moisture with significant fluctuations (55%–85% soil moisture), while Treatment 2 (T2) maintained optimal and stable moisture levels (70%–85%). …”
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Ensemble Transformer–Based Detection of Fake and AI–Generated News by Md. Ishraquzzaman, Mohammed Ashraful Islam Chowdhury, Shahreen Rahman, Riasat Khan

“…This work leverages advanced natural language processing, machine learning, and deep learning algorithms to effectively detect fake and AI–generated content. …”
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Prediction of hypertensive disorders in pregnant women in the «gray» risk zone following combined first-trimester screening by N. V. Mostova, V. V. Kovalev, E. V. Kudryavtseva

“…Group 1 consisted of female patients at high РЕ risk (1:100 and greater), while female patients at moderate risk (1:101–1:250) and low risk (below 1:250) were included into Group 2 and Group 3, respectively. …”
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Retrieval of top-of-atmosphere fluxes from combined EarthCARE lidar, imager, and broadband radiometer observations: the BMA-FLX product by A. Velázquez Blázquez, C. Domenech, E. Baudrez, N. Clerbaux, C. Salas Molar, N. Madenach

“…The radiance-to-flux conversion algorithms have been successfully validated through end-to-end verification using L1 and L2 synthetic data for three EarthCARE orbits. …”
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Streaming LiDAR Scene Flow Estimation by Mazen Abdelfattah, Z. Jane Wang, Rabab Ward

“…This achieves substantial speedups while maintaining, and in some cases surpassing, full-scan accuracy. …”
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The Philosophy of Semar as an Ethical Framework for the Use of Artificial Intelligence by Mohamad Khusnial Muhtar, Naufal Robbiqis Dwi

“…<div>Artificial intelligence (AI) is a multidimensional phenomenon that profoundly impacts various aspects of&nbsp;<span style="font-size: 1rem;">modern human life. While global discussions on AI ethics have predominantly centered on Western&nbsp;</span><span style="font-size: 1rem;">perspectives, this study explores ethical AI development through the lens of Semar philosophy,&nbsp;</span><span style="font-size: 1rem;">representing the local wisdom of Nusantara. …”
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Unmanned Aerial Surveillance and Tracking System in Forest Areas for Poachers and Wildlife by R. G. Sangeetha, Yash Srivastava, C. Hemanth, Harsh Sankar Naicker, Abhijith P. Kumar, Sreejith Vidhyadharan

“…Using a robust two-fold collision avoidance system, the drone travels autonomously while avoiding obstacles in the dense forest cover. …”
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