The 3D tooth model segmentation method based on GAC+PointMLP network by Jianjun Chen, Liyuan Zheng, Huilai Zou, Jiafa Mao, Weiguo Sheng

“…Compared to other traditional segmentation algorithms, the proposed method shows improvements of 1.1, 2.04, 1.06, 2.2, and 1.8 percentage points in Overall Accuracy (OA), Sensitivity (SEN), Positive Predictive Value (PPV), and Intersection Over Union (IoU), respectively. …”
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Explainable AI-based suicidal and non-suicidal ideations detection from social media text with enhanced ensemble technique by Daniyal Alghazzawi, Hayat Ullah, Naila Tabassum, Sahar K. Badri, Muhammad Zubair Asghar

“…Our methodology, along with an updated ensemble method, bridges the gap between Explainable AI and leverages a variety of machine learning algorithms to improve predictive accuracy. By leveraging Explainable AI’s interpretability to analyze the features, the model elucidates the reasoning behind its classifications leading to a comprehension of hidden patterns associated with suicidal ideations. …”
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Optimal Placement of Wind Power System Using Machine Learning by Abdul Karim, Muhammad Amir Raza, Darakhshan Ara, Muhammad Shahid, Shakir Ali Soomro

“…Hence, this study, proposed a plan for the installation of wind turbines in Doha Qatar, and forecasted the future temperature and wind speed for the optimal placement of large-scale wind turbines using the Pythons algorithms namely, Long Short-Term Memory (LSTM), Prophet (PT), Support Vector Regression (SVR), Linear Regression (LR), Seasonal Autoregressive Integrated Moving Average with External Factors (SARIMAX), and K-Nearest Neighbors (KNN). …”
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Numerical Simulation of Earthquake Impacts on Marine Structures: A Comprehensive Review by Adel Kabi, Jersson X. Leon-Medina, Francesc Pozo

“…However, challenges persist in areas such as computational efficiency and algorithmic limitations. Key findings highlight the ability of these models to accurately simulate primary forces during seismic events and secondary effects, such as wave-induced loads. …”
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Hilbert-Huang Transform and machine learning based electromechanical analysis of induction machine under power quality disturbances by V. Indragandhi, R. Senthil Kumar, R. Saranya

“…Monitoring and predicting Power Quality (PQ) is crucial for quickly minimizing risk, protecting induction machines (IMs), and increasing productivity. …”
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Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke by Gianluca Brugnara, Michael Baumgartner, Edwin David Scholze, Katerina Deike-Hofmann, Klaus Kades, Jonas Scherer, Stefan Denner, Hagen Meredig, Aditya Rastogi, Mustafa Ahmed Mahmutoglu, Christian Ulfert, Ulf Neuberger, Silvia Schönenberger, Kai Schlamp, Zeynep Bendella, Thomas Pinetz, Carsten Schmeel, Wolfgang Wick, Peter A. Ringleb, Ralf Floca, Markus Möhlenbruch, Alexander Radbruch, Martin Bendszus, Klaus Maier-Hein, Philipp Vollmuth

“…We provide an imaging platform ( https://stroke.ccibonn.ai/ ) for online processing of medical imaging data with the developed ANN, including provisions for data crowdsourcing, which will allow continuous refinements and serve as a blueprint to build robust and generalizable AI algorithms.…”
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From word models to executable models of signaling networks using automated assembly by Benjamin M Gyori, John A Bachman, Kartik Subramanian, Jeremy L Muhlich, Lucian Galescu, Peter K Sorger

“…Molecular mechanisms described in simple English are read by natural language processing algorithms, converted into an intermediate representation, and assembled into executable or network models. …”
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Artificial intelligence in respiratory care by Manjush Karthika, Jithin K. Sreedharan, Madhuragauri Shevade, Chris Sara Mathew, Santosh Ray

“…AI algorithms are widely studied in areas like mechanical ventilation, sleep medicine, lung ultrasound, and pulmonary function diagnostics and the results are found to be promising. …”
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BREAST-CAD: A Computer-Aided Diagnosis System for Breast Cancer Detection Using Machine Learning by Riyam M. Masoud, Ramadan Madi Ali Bakir, M. Sabry Saraya, Sarah M. Ayyad

“…Our approach follows a three-phase methodology: Initially, a comprehensive literature review between 2000 and 2024 informed the choice of a suitable dataset and the selection of Naive Bayes (NB), K-Nearest Neighbors (KNN), Support Vector Machines (SVM), and Decision Trees (DT) Machine Learning (ML) algorithms. Subsequently, the dataset was preprocessed and the four ML models were trained and validated, with the DT model achieving superior accuracy. …”
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High-resolution Annual Dynamic dataset of Curve Number from 2008 to 2021 over Conterminous United States by Qiong Wu, John J. Ramirez Avila, Jia Yang, Cunxiong Ji, Shanmin Fang

“…This developed CN dataset can be used as input for hydrological models or machine learning algorithms to simulate rainfall-runoff across multiple spatiotemporal scales.…”
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Machine Learning-Based Analysis of Travel Mode Preferences: Neural and Boosting Model Comparison Using Stated Preference Data from Thailand’s Emerging High-Speed Rail Network by Chinnakrit Banyong, Natthaporn Hantanong, Supanida Nanthawong, Chamroeun Se, Panuwat Wisutwattanasak, Thanapong Champahom, Vatanavongs Ratanavaraha, Sajjakaj Jomnonkwao

“…It conducts a comparative assessment of predictive capabilities between the conventional Multinomial Logit (MNL) framework and advanced data-driven methodologies, including gradient boosting algorithms (Extreme Gradient Boosting, Light Gradient Boosting Machine, Categorical Boosting) and neural network architectures (Deep Neural Network, Convolutional Neural Network). …”
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Role of Artificial Intelligence and Personalized Medicine in Enhancing HIV Management and Treatment Outcomes by Ashok Kumar Sah, Rabab H. Elshaikh, Manar G. Shalabi, Anass M. Abbas, Pranav Kumar Prabhakar, Asaad M. A. Babker, Ranjay Kumar Choudhary, Vikash Gaur, Ajab Singh Choudhary, Shagun Agarwal

“…Despite these innovations, challenges such as data privacy, algorithmic bias, and the need for clinical validation remain. …”
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Immune status assessment based on plasma proteomics with meta graph convolutional networks by Min Zhang, Nan Xu, Qi Cheng, Jing Ye, Shiwei Wu, Haoliang Liu, Chengkui Zhao, Lei Yu, Weixing Feng

“…Abstract Plasma proteins, especially immune-related proteins, are vital for assessing immune health and predicting disease risks. Despite their significance, the link between these proteins and systemic immune function remains unclear. …”
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Unsupervised Clustering of Cell Populations in Germinal Centers Using Multiplexed Immunofluorescence by Simon Burgermeister, Michail Orfanakis, Spiros Georgakis, Cloe Brenna, Helen Lindsay, Craig Fenwick, Giuseppe Pantaleo, Raphael Gottardo, Constantinos Petrovas

“…We evaluate multiple clustering algorithms and find that k-means clustering provides the most effective separation of distinct cell subsets. …”
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Advancements in Chemical Materials: Exploring Smart Storage Equipment and Protection Systems (Review) by Samah Kamil, Mohammed Al-Turfi, Riyadh Almukhtar

“…Results showed breakthroughs in sensor technologies, systems integration, and AI algorithms for real-time storage facility monitoring, danger identification, and predictive analytics. …”
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Trustworthiness of Deep Learning Under Adversarial Attacks in Power Systems by Dowens Nicolas, Kevin Orozco, Steve Mathew, Yi Wang, Wafa Elmannai, George C. Giakos

“…Emphasizing the inherent requirement of robust defense, this initiative lays the groundwork for follow-on initiatives to incorporate security and resilience into ML and DL algorithms and ensure mission-critical AI system dependability.…”
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Historical Reconstruction of Astronaut Cancer Risk: Context for Recent Solar Minima by Tony C. Slaba

“…To provide additional context for this level of variation, two different nuclear interaction models are used within the radiation transport algorithms used to propagate GCR ions and secondary particles through shielding and tissue. …”
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Machine learning discovery of the dielectric properties of strontium-containing condensed matter by Dongyang Huang, Jiaxing Fu, Chenghao Yu

“…Traditional theoretical predictions or first-principles calculations of dielectric constants are often challenging and require significant time and computational resources. …”
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A Review of Modeling and Control Techniques for Unmanned Aerial Vehicles by Elisabeth Andarge Gedefaw, Nardos Belay Abera, Chala Merga Abdissa

“…The findings highlight that hybrid control strategies incorporating adaptive mechanisms, learning‐based algorithms, and quaternion‐based modeling offer significant potential for enhancing autonomy and control. …”
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Comparison of Random Forest, XGBoost, and LightGBM Methods for the Human Development Index Classification by Yunna Mentari Indah, Rafika Aristawidya, Anwar Fitrianto, Erfiani Erfiani, L.M. Risman Dwi Jumansyah

“…The study applied these algorithms to analyze the most influential variables affecting HDI. …”
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