Explainable machine learning for predicting ICU mortality in myocardial infarction patients using pseudo-dynamic data by Munib Mesinovic, Peter Watkinson, Tingting Zhu

“…We compare standard supervised machine learning algorithms with novel tabular deep learning approaches and find that an integrated XGBoost model in our EHR time-series extraction framework (XMI-ICU) performs best. …”
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Bird Species Detection Net: Bird Species Detection Based on the Extraction of Local Details and Global Information Using a Dual-Feature Mixer by Chaoyang Li, Zhipeng He, Kai Lu, Chaoyang Fang

“…Currently, most deep learning algorithms focus on designing local feature extraction modules while ignoring the importance of global information. …”
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AI and consumer behavior: Trends, technologies, and future directions from a scopus-based systematic review by Aditya Nanda Riandhi, Muhammad Rifqi Arviansyah, Mery Citra Sondari

“…Consumer attitudes (trust, privacy) and behavioral intentions emerge as primary mediators of AI adoption, while ethical concerns underline the need for open algorithmic architectures. …”
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Unraveling the Reshaping of Human Resource Management Function: the mediating role of artificial intelligence by Samuel Bangura, Anos Chitamba Chitamba, Lucia Zithobile Ngidi, Sizwe Mbona

“…However, the study also identifies potential challenges associated with AI adoption, including concerns related to algorithmic bias, data privacy, transparency, and employee apprehensions. …”
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Reinforcement learning in artificial intelligence and neurobiology by Tursun Alkam, Andrew H Van Benschoten, Ebrahim Tarshizi

“…Empirical studies reveal neural correlates of RL algorithms in the basal ganglia, prefrontal cortex, and hippocampus, supporting their roles in planning, memory, and decision-making. …”
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Bio-Inspired Traffic Pattern Generation for Multi-AMR Systems by Rok Vrabič, Andreja Malus, Jure Dvoršak, Gregor Klančar, Tena Žužek

“…Compared to the existing approaches, the proposed approach addresses the entire intralogistic problem, including plant layout, task distribution, release and dispatching algorithms, and fleet size. Its autonomous movement rule generation and low computational complexity make it well suited for dynamic intralogistic environments. …”
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Sex bias consideration in healthcare machine-learning research: a systematic review in rheumatoid arthritis by Coziana Ciurtin, Shruti Turner, Anahita Talwar, Claudia Maw, Georgina Quayle, Thomas N Watt, Sunir Gohil, Emma Duckworth

“…Potential sex bias in input variables was acknowledged in one paper, while six papers commented on sex bias in their output variables, predominantly disease activity scores. …”
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Petri graph neural networks advance learning higher order multimodal complex interactions in graph structured data by Alma Ademovic Tahirovic, David Angeli, Adnan Tahirovic, Goran Strbac

“…The work opens new directions in learning over complex structures, transcending transformer-based and traditional hypergraph-based algorithms. We validate results through theoretical analysis and real-world experiments, while demonstrating superior performance in, e.g., stock market prediction.…”
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Precision Medicine in Lung Cancer Screening: A Paradigm Shift in Early Detection—Precision Screening for Lung Cancer by Hsin-Hung Chen, Yun-Ju Wu, Fu-Zong Wu

“…Lung cancer remains the leading cause of cancer-related mortality globally, largely due to late-stage diagnoses. While low-dose computed tomography (LDCT) has improved early detection and reduced mortality in high-risk populations, traditional screening strategies often adopt a one-size-fits-all approach based primarily on age and smoking history. …”
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A Novel Ensemble of Deep Learning Approach for Cybersecurity Intrusion Detection with Explainable Artificial Intelligence by Abdullah Alabdulatif

“…Recursive Feature Elimination is utilized for optimal feature selection, while SHapley Additive exPlanations (SHAP) provide both global and local interpretability of the model’s decisions. …”
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Vision-Based 6D Pose Analytics Solution for High-Precision Industrial Robot Pick-and-Place Applications by Balamurugan Balasubramanian, Kamil Cetin

“…The Z-position of the object is calculated from the camera’s intensity data, while the remaining X-Y rotation angles are determined using the angle-of-inclination analytics method. …”
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Large Language Models in Medical Chatbots: Opportunities, Challenges, and the Need to Address AI Risks by James C. L. Chow, Kay Li

“…These include hallucinations (the generation of factually incorrect or misleading content by an AI model), algorithmic biases, privacy risks, and a lack of regulatory clarity. …”
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Enhancing Autonomous Driving Perception: A Practical Approach to Event-Based Object Detection in CARLA and ROS by Jingxiang Feng, Peiran Zhao, Haoran Zheng, Jessada Konpang, Adisorn Sirikham, Phuri Kalnaowakul

“…In contrast, event-based cameras, which operate asynchronously and capture rapid changes with high temporal resolution and expansive dynamic range, offer a promising augmentation. While the previous research on event-based object detection has predominantly focused on algorithmic enhancements via advanced preprocessing and network optimizations to improve detection accuracy, the practical engineering and integration challenges of deploying these sensors in real-world systems remain underexplored. …”
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TEACHER EDUCATION AND FEATURES OF THE CONTEMPORARY EDUCATIONAL CONTEXT by Irina G. Zakharova

“…The research results can be used while developing basic educational programs of teacher education. …”
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An Empirical Comparison of Machine Learning and Deep Learning Models for Automated Fake News Detection by Yexin Tian, Shuo Xu, Yuchen Cao, Zhongyan Wang, Zijing Wei

“…Our results show that transformer-based models, especially ALBERT, achieve state-of-the-art performance (macro F1 up to 0.99) with rich context, while classical ensembles remain viable for constrained settings. …”
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Behavioral economics: science or exoticism? by I. N. Drogobytsky

“…While studying economics as a science and an active sphere of human activity, scientists aim to give consistency to their knowledge, ensure that they are adequate and constructive. …”
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The comparison of distance metrics in descriptor matching methods utilised in TLS-SfM point cloud registration by Markiewicz Jakub

“…Descriptor matching in SfM-TLS typically employs the L2 norm to measure Euclidean distances between features, valued for its simplicity and compatibility with algorithms like SIFT. This study investigates the influence of various distance metrics on descriptor matching during the correspondence search stage of SfM-TLS. …”
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Artificial intelligence: protection and defence of human rights (ethical aspect) by Yu. M. Zhornokui

“…Work should focus on developing an ethical framework for artificial intelligence systems that prioritises transparency, fairness and accountability, while minimising potential negative impacts on human rights.…”
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Automated Microservices Identification Through Business Process Analysis: A Semantic-Driven Clustering Approach by Idris Oumoussa, Rajaa Saidi

“…The rise of microservice architectures has further evolved software development practices, building upon the foundation established by web services in breaking down monolithic systems, while offering more finely detailed, coherent, and loosely interconnected services. …”
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A Machine Learning Framework for Student Retention Policy Development: A Case Study by Sidika Hoca, Nazife Dimililer

“…This study presents a machine learning framework for predicting and visualizing students at risk of dropping out. While most previous work relies on wide-ranging data from numerous sources such as surveys, enrolment, and learning management systems, making the process complex and time-consuming, the current study uses minimal data that are readily available in any registration system. …”
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