Explainable Artificial Intelligence Models for Predicting Depression Based on Polysomnographic Phenotypes by Doljinsuren Enkhbayar, Jaehoon Ko, Somin Oh, Rumana Ferdushi, Jaesoo Kim, Jaehong Key, Erdenebayar Urtnasan

“…Advanced machine learning algorithms such as random forest, extreme gradient boosting, categorical boosting, and light gradient boosting machines were employed to train and validate the predictive AI models. …”
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Remote Sensing Image Segmentation Using Vision Mamba and Multi-Scale Multi-Frequency Feature Fusion by Yice Cao, Chenchen Liu, Zhenhua Wu, Lei Zhang, Lixia Yang

“…Although segmentation algorithms based on convolutional neural networks (CNNs) or Transformers have achieved significant performance improvements, the trade-off between segmentation precision and computational complexity remains a key limitation for practical applications. …”
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Identification of cell chemistries in lithium-ion batteries: Improving the assessment for recycling and second-life by Christopher Wett, Jörg Lampe, Dominik Görick, Thomas Seeger, Bugra Turan

“…The dV/dQ characteristics are chosen as features and four machine learning algorithms are trained on different lengths of OCV curves. …”
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Wearable sensor-based fall detection for elderly care using ensemble machine learning techniques by Ch Gangadhar, P Pavithra Roy, R. Dinesh Kumar, Janjhyam Venkata Naga Ramesh, S. Ravikanth, N. Akhila

“…The suggested method employed RF to reliably retrieve features from speedometer and inertial facts, while SVM provides an estimator and classification-capable method. …”
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Reference Gene Selection for Quantitative Real-Time RT-PCR Normalization in Iris. lactea var. chinensis Roots under Cadmium, Lead, and Salt Stress Conditions by Chun-Sun Gu, Liang-qin Liu, Chen Xu, Yan-hai Zhao, Xu-dong Zhu, Su-Zhen Huang

“…GeNorm and NormFinder algorithms were used to assess the suitable reference genes. …”
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Remote monitoring of Tai Chi balance training interventions in older adults using wearable sensors and machine learning by Giulia Corniani, Stefano Sapienza, Gloria Vergara-Diaz, Andrea Valerio, Ashkan Vaziri, Paolo Bonato, Peter M. Wayne

“…Data were collected from 32 participants with inertial measurement units (IMUs) while performing six Tai Chi movements evaluated and scored for adherence and proficiency by experts. …”
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Reallocating diabetes-related garbage codes to improve mortality estimates: a case study in Weifang, China by Xiao Zhang, Wenyi Yang, Jingxin Wang, Limei Ai, Min Chen, Chunping Wang, Xia Wan

“…Based on the reallocated data, crude DM mortality rates rose from 7.64 to 17.75 per 100,000 between 2010 and 2022, with males experiencing a greater overall increase than females. While no new algorithms were developed, this study demonstrates how internationally recommended coding standards—often neglected in routine subnational settings—can be systematically and rigorously applied to improve DM mortality surveillance. …”
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Mixed Reality Human–Robot Interface With Adaptive Communications Congestion Control for the Teleoperation of Mobile Redundant Manipulators in Hazardous Environments by Krzysztof Adam Szczurek, Raul Marin Prades, Eloise Matheson, Jose Rodriguez-Nogueira, Mario Di Castro

“…The teleoperator was provided with immersive interactions while preserving precise positioning of the robot. …”
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Artificial Intelligence Approaches for Geographic Atrophy Segmentation: A Systematic Review and Meta-Analysis by Aikaterini Chatzara, Eirini Maliagkani, Dimitra Mitsopoulou, Andreas Katsimpris, Ioannis D. Apostolopoulos, Elpiniki Papageorgiou, Ilias Georgalas

“…This systematic review evaluates the performance of AI algorithms for GA segmentation and highlights their key limitations from the literature. …”
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Sustainability-driven fertilizer recommender system for coffee crops using case-based reasoning approach by Edinson David León Chilito, Juan Fernando Casanova Olaya, Juan Fernando Casanova Olaya, Juan Carlos Corrales, Cristhian Figueroa

“…Future work will expand the case base and refine recommender algorithms to improve accuracy and usability.…”
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The future of AI in government services and global risks: insights from design fictions by Pedro Vitor Marques Nascimento, Paloma Beatriz Belchior de Siqueira, Nathalia Chrispim, Ramon Miranda Chaves, Carlos Eduardo Barbosa, Jano Moreira de Souza

“…The findings highlight three critical dilemmas: (1) AI’s dual role in enhancing efficiency while exacerbating algorithmic bias and surveillance concerns; (2) the potential displacement of human roles in public services, raising questions about accountability and transparency; and (3) the ethical trade-offs in AI-driven decision-making, particularly in law enforcement, healthcare, and education. …”
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Artificial Neural Network for Air Pollutant Concentration Predictions Based on Aircraft Trajectories over Suvarnabhumi International Airport by Patcharin Kamsing, Chunxiang Cao, Wuttichai Boonpook, Sornkitja Boonprong, Min Xu, Pisit Boonsrimuang

“…The results demonstrate that the mean square errors (MSEs) of the predicted models for CO and PM_2.5 have acceptable values of 51.7622 and 53.9682, respectively, while the predicted model for NO₂ and PM₁₀ has MSEs of 139.6674 and 124.2517, respectively. …”
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Optimizing Immunotherapy: The Synergy of Immune Checkpoint Inhibitors with Artificial Intelligence in Melanoma Treatment by Mohammad Saleem, Abigail E. Watson, Aisha Anwaar, Ahmad Omar Jasser, Nabiha Yusuf

“…These findings underscore the potential of AI-driven approaches to refine biomarker identification, treatment prediction, and patient stratification in melanoma immunotherapy. While promising, clinical validation and implementation challenges remain.…”
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Machine Learning Applications in Use-Wear Analysis: A Critical Review by Anastasia Eleftheriadou, Shannon P. McPherron, João Marreiros

“…Recently, machine learning (ML) has been employed as a promising method for automating and standardizing the identification of these traces. While the number of use-wear analysts using ML continues to grow, discussions regarding the effectiveness and appropriate implementation of these methods are ongoing. …”
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Estimation of water storage changes in a tropical lake-floodplain system through remote sensing by Thijs de Klein, Victor Bense, Syed Mustafa

“…Results suggest that climate change effects and anthropogenic activities may have little short-term impact on the lake’s dry season volume, while altering groundwater recharge may have more significant long-term effects.…”
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Autonomous detection of nail disorders using a hybrid capsule CNN: a novel deep learning approach for early diagnosis by Gunjan Shandilya, Sheifali Gupta, Salil Bharany, Ateeq Ur Rehman, Upinder Kaur, Hafizan Mat Som, Seada Hussen

“…The purpose of this research is to offer novel deep-learning algorithms that target the autonomous categorization of six forms of nail disorders by employing images: Blue Finger, Clubbing, Pitting, Onychogryphosis, Acral Lentiginous Melanoma, and Normal Nail or Healthy Nail Appearance. …”
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AI Techniques and Applications for Online Social Networks and Media: Insights From BERTopic Modeling by Prema Nedungadi, G. Veena, Kai-Yu Tang, Remya R. K. Menon, Raghu Raman

“…Although AI techniques and multimodal frameworks have significantly improved content personalization, challenges like algorithmic bias and echo chambers remain. To address these, the implementation of fairness-aware learning models is recommended to ensure personalization stays ethical. …”
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Optimized Wireless Sensor Network Architecture for AI-Based Wildfire Detection in Remote Areas by Safiah Almarri, Hur Al Safwan, Shahd Al Qisoom, Soufien Gdaim, Abdelkrim Zitouni

“…The system also integrates artificial intelligence (AI) algorithms (multiclass logistic regression) to process sensor data and predict fire risk levels with 99.97% accuracy, enabling proactive wildfire mitigation. …”
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A novel pressure control method for nonlinear shell-and-tube steam condenser system via electric eel foraging optimizer by Serdar Ekinci, Cebrail Turkeri, Davut Izci, Laith Abualigah, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

“…However, traditional controllers (PI, PD, PID) struggle with nonlinearities and external disturbances, while classical tuning methods (Ziegler-Nichols, and Cohen-Coon) fail to provide optimal parameter selection. …”
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Enhanced Collaborative Edge Intelligence for Explainable and Transferable Image Recognition in 6G-Aided IIoT by Chen Chen, Ze Sun, Jiale Zhang, Junwei Dong, Peng Zhang, Jie Guo

“…IRCE leverages edge intelligence to optimize real-time performance while reducing computational costs and enhancing scalability. …”
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