An Automated Image-Based Dietary Assessment System for Mediterranean Foods by Fotios S. Konstantakopoulos, Eleni I. Georga, Dimitrios I. Fotiadis

“…The proposed volume estimation subsystem uses stereo vision techniques and algorithms, and needs the input of two food images to reconstruct the point cloud of the food and to compute its quantity. …”
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Limited Performance of Machine Learning Models Developed Based on Demographic and Laboratory Data Obtained Before Primary Treatment to Predict Coronary Aneurysms by Mi-Jin Kim, Gi-Beom Kim, Dongha Yang, Yeon-Jin Jang, Jeong-Jin Yu

“…Various supervised machine learning algorithms were applied to develop a model for predicting CAA. …”
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Priorities of ensuring hygiene and occupational safety of medical personnel and the resilience of healthcare facilities in emergency situations by R. P. Brukhno, O. P. Yavorovskyi, Yu. M. Skaletskyi, T. O. Zinchenko

“…There is an urgent need to develop clear response algorithms for healthcare facilities to cope with emergency situations that could influence them. …”
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Optimising management against dynamic threats: A spatially explicit approach based on integer programming by José Salgado‐Rojas, Virgilio Hermoso, Eduardo Álvarez‐Miranda

“…Employing a Warm‐start algorithmic strategy ensures rapid generation of feasible solutions, enhancing the model's practical applicability and scalability. …”
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Lightweight and robust ship detection method driven by self-attention mechanism by Feng MA, Zihui SHI, Jie SUN, Chen CHEN, Xianbin MAO, Xinping YAN

“…During testing, the proposed method demonstrates superior overall ship detection performance compared to other algorithms, with a mAP of 92.9%, a precision rate of 92.1%, and a parameter size of 35 366 310. …”
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Machine learning for asphaltene polarizability: Evaluating molecular descriptors by Arun K. Sharma, Owen McMillan, Selsela Arsala, Supreet Gandhok, Rylend Young

“…The Wolfram Language’s Predict function evaluated multiple machine learning algorithms—including Random Forest, Decision Tree, Gradient Boosted Trees, Nearest Neighbors, Linear Regression, Gaussian Process, and Neural Network—through an automated model selection process, serving as an AutoML framework. …”
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Predicting PTSD development with early post-trauma assessments: a proof-of-concept for a concise tree-based classification method by Chia-Hao Shih, Elyssa Charlotte Feuer, Ben Kurzion, Kevin Xu, Hong Xie, Stephen R. Grider, Xin Wang

“…The performance of the CART model was benchmarked against two of the most powerful and widely used machine learning algorithms in the field, Random Forest (RF) and Gradient Boosting (GB) models.Results: The CART model, which incorporates just three critical questions from established assessments, predicted PTSD development with performance closely matched to that of the RF and GB models. …”
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Automated interpretation of deep learning-based water quality assessment system for enhanced environmental management decisions by Javed Mallick, Saeed Alqadhi, Majed Alsubih, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…SHAP analysis highlighted chloride, sulphate, and total dissolved solids as key contributors to the WQI, while sodium and calcium were significant for the sodium adsorption ratio. …”
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Disinformation in the Digital Age: Climate Change, Media Dynamics, and Strategies for Resilience by Andrea Tomassi, Andrea Falegnami, Elpidio Romano

“…Our findings indicate that social media algorithms and user dynamics can amplify false scientific claims, as seen in case studies of viral misinformation campaigns on vaccines and climate change. …”
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Prediction of in-hospital mortality in patients with ST-segment elevation acute myocardial infarction after percutaneous coronary intervention by B. I. Geltser, K. I. Shahgeldyan, I. G. Domzhalov, N. S. Kuksin, E. A. Kokarev, V. N. Kotelnikov, V. Yu. Rublev

“…Two groups of persons were identified, the first of which consisted of 321 (6,8%) patients who died in the hospital, while the second — 4413 (93,2%) patients with a favorable PCI outcome. …”
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MAST Kinases’ Function and Regulation: Insights from Structural Modeling and Disease Mutations by Michael C. Lemke, Nithin R. Avala, Michael T. Rader, Stefan R. Hargett, Daniel S. Lank, Brandon D. Seltzer, Thurl E. Harris

“…We also estimate the functional consequences of disease point mutations on protein stability by integrating predictive algorithms and AlphaFold. <b>Results</b>: Higher-order organisms often have multiple MASTs and a single MASTL kinase. …”
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DIGITAL TRANSFORMATION OF BUSINESS MANAGEMENT: INNOVATIVE MODELS, FORECAST SCENARIOS AND CURRENT CHALLENGES OF ECONOMY MODERNIZATION by I.V. Burtnyak, T.V. Khaludilo

“…Key aspects of digitalization, including the integration of innovative technologies into management systems, the utilization of computer algorithms for processing large volumes of data, and the creation of interactive platforms for prompt decision-making, have been examined in the article. …”
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SSMM: Semi-supervised manifold method with spatial-spectral self-training and regularized metric constraints for hyperspectral image dimensionality reduction by Bei Zhu, Yao Jin, Xuehua Guan, Yanni Dong

“…In addition, to divide the sample categories while dimensionality reduction, low-dimensional manifold embedding is constructed and the metric constraint is imposed on the manifolds. …”
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A non-sub-sampled shearlet transform-based deep learning sub band enhancement and fusion method for multi-modal images by Sudhakar Sengan, Praveen Gugulothu, Roobaea Alroobaea, Julian L. Webber, Abolfazl Mehbodniya, Amr Yousef

“…The enhanced LFCs are fused using an AlexNet-based activity-level fusion model, while the enhanced HFCs are combined using a Pulse Coupled Neural Network (PCNN) guided by a Novel Sum-Modified Laplacian (NSML) metric. …”
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A deep learning model for predicting systemic lupus erythematosus-associated epitopes by Jiale He, Zixia Liu, Xiaopo Tang

“…Results The hybrid model outperformed both baseline machine learning algorithms and ablated versions of itself. It achieved a ROCAUC of 0.9506 and an F1-score of 0.8333 on the SLE epitope prediction task. …”
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Cross-dimensional adaptivity research on a 3D earth observation data cube model by Yu Jinsongdi, Cui Zhanying, Baumann Peter, Tong Ruiju, Wei Dandan, Luo Yuan

“…This becomes feasible by applying suitable serialization algorithms. This study demonstrates that data cubes can be successfully mapped into the proposed 3D adaptive data cube, achieving interoperability under specific conditions. …”
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Assessing the deep learning based image quality enhancements for the BGO based GE omni legend PET/CT by Meysam Dadgar, Amaryllis Verstraete, Jens Maebe, Yves D’Asseler, Stefaan Vandenberghe

“…The exemplary patient study shows that the noise was suppressed for all deep learning cases, but low precision deep learning also reduced the lesion contrast (about −30 $$\%$$ % ), while high precision deep learning increased the contrast (about 10 $$\%$$ % ). …”
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OCTNet: A Modified Multi-Scale Attention Feature Fusion Network with InceptionV3 for Retinal OCT Image Classification by Irshad Khalil, Asif Mehmood, Hyunchul Kim, Jungsuk Kim

“…Traditional approaches rely on machine learning for feature extraction, while deep learning methods utilize data-driven classification model training. …”
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Automated Calibration of SWMM for Improved Stormwater Model Development and Application by Hossein Ahmadi, Durelle Scott, David J. Sample, Mina Shahed Behrouz

“…During multi-objective optimization calibration, the model achieved NSE, PBIAS, and RSR values of 0.73, 17.1, and 0.52, respectively; while the validation period recorded values of 0.86, 13.1, and 0.37, respectively. …”
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Real-time monitoring of maize phenology using ground camera fusion information by Qi Zhao, Yonghua Qu, Dongyi Liu

“…The SEL method effectively improved the accuracy and efficiency of BBCH estimates while demonstrating good stability and generalization ability. …”
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