Assessing the Duration of the Paleocene‐Eocene Thermal Maximum by Victor A. Piedrahita, David Heslop, Andrew P. Roberts, Eelco J. Rohling, Simone Galeotti, Fabio Florindo, Jinhua Li

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Spatiotemporal Flood Hazard Classification in Bangkok Using Graph Convolutional Network and Temporal Fusion Transformer by Pakpoom Chaimook, Nirattaya Khamsemanan, Cholwich Nattee, Alice Sharp

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Joint Multifractal Analysis and Source Testing of River Level Records Based on Multifractal Detrended Cross-Correlation Analysis by Liang Wu, Manling Wang, Tongzhou Zhao

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Heterogeneous transfer learning model for improving the classification performance of fNIRS signals in motor imagery among cross-subject stroke patients by Jin Feng, YunDe Li, ZiJun Huang, Yehang Chen, SenLiang Lu, RongLiang Hu, QingHui Hu, YuYao Chen, XiMiao Wang, Yong Fan, Jing He

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Digital Staining Algorithm for Multi-Domain Transformation of Unstained Images by Dong-Bum Kim, Jong-Ha Lee

“…Digital staining is an artificial intelligence-based technology that replaces the conventional staining process. …”
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Federated learning for privacy-enhanced mental health prediction with multimodal data integration by Parul Dubey, Pushkar Dubey, Pitshou N. Bokoro

“…Mental health diagnostics, an evolving domain in healthcare, aims to enhance early detection and intervention strategies. The integration of artificial intelligence (AI) and machine learning has facilitated advanced predictive models, but concerns related to data privacy and security remain significant challenges. …”
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Thermographic Insights into Degenerative Spinal Disorders: Evaluating the Diagnostic Potential of Digital Infrared Thermography Imaging by Sathish Muthu, Guna Pratheep Kalanchiam, Ashok Shyam

“…While DITI offers advantages such as real-time functional assessment, cost-effectiveness, and early disease detection, challenges related to standardization, environmental variability, and specificity persist. …”
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Deposition Characteristics of Air-Assisted Sprayer Based on Canopy Volume and Leaf Area of Orchard Trees by Chenchen Gu, Jiahui Sun, Si Li, Shuo Yang, Wei Zou, Changyuan Zhai

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On the Prediction and Forecasting of PMs and Air Pollution: An Application of Deep Hybrid AI-Based Models by Youness El Mghouchi, Mihaela Tinca Udristioiu

“…This study aims to develop robust predictive and forecasting models for hourly PM concentrations in Craiova, Romania, using advanced hybrid Artificial Intelligence (AI) approaches. A five-year dataset (2020–2024), comprising 20 meteorological and pollution-related variables recorded by four air quality monitoring stations, was analyzed. …”
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A novel dynamic machine learning-based explainable fusion monitoring: application to industrial and chemical processes by Husnain Ali, Rizwan Safdar, Yuanqiang Zhou, Yuan Yao, Le Yao, Zheng Zhang, Weilong Ding, Furong Gao

“…Traditional monitoring techniques for automatic anomaly detection, identifying the potential variables, and root cause analysis for fault information are not intelligent enough to tackle the intricate problems of real-time practices in the industrial and chemical sectors. …”
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Assessing the representativeness of large medical data using population stability index by Sheng-Chieh Lu, Wenye Song, Andre Pfob, Chris Gibbons

“…In this study, we aimed to examine the capability of population stability index (PSI), a popular metric to assess data drift for artificial intelligence studies, in detecting sample differences using population-based data. …”
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Evaluating Assistive Technology Outcomes in Boccia Athletes with Disabilities Using AI-Based Kinematic Analysis by Wann-Yun Shieh, Yan-Ying Ju, Shiu-Yuan Yang, I-Chun Chen, Hsin-Yi Kathy Cheng

“…AI-enhanced 2D and 3D pose estimation methods were applied to assess throwing strategies and motor variability. ViTPose outperformed OpenPose in joint detection accuracy (F1-score: 85% vs. 79.5%), while Lifting improved 3D estimation by reducing joint position error by 16%. …”
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Predicting the insulating paper state of the power transformer based on XGBoost/LightGBM models by Sherif S. M. Ghoneim, Mohammed Baz, Ali Alzaed, Yohannes Tesfaye Zewdie

“…The utilities keen on the contentious operation of the power network, so early detection of the transformer faults avoiding the undesirable outage of the transformer from the service. …”
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Brain computer interface based emotion recognition with error analysis and challenges: an interdisciplinary review by Niharika Gudikandula, Ravichander Janapati, Rakesh Sengupta, Sridhar Chintala

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An XAI Approach to Melanoma Diagnosis: Explaining the Output of Convolutional Neural Networks with Feature Injection by Flavia Grignaffini, Enrico De Santis, Fabrizio Frezza, Antonello Rizzi

“…Computer-aided diagnosis (CAD) systems, which combine medical image processing with artificial intelligence (AI) to support experts in diagnosing various diseases, emerged from the need to solve some of the problems associated with medical diagnosis, such as long timelines and operator-related variability. …”
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Spatio-temporal expansion patterns and influencing factors in China's new local retail industry: A case study of Luckin Coffee. by FengXun Qi, WeiShan Qin, Xiaohan Li

“…with the increased penetration of the Internet, artificial intelligence, and other technologies, New Retail, an emerging commercial sector in cities, has gained significant momentum. …”
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Exploring the Streetscape Perceptions from the Perspective of Salient Landscape Element Combination: An Interpretable Machine Learning Approach for Optimizing Visual Quality of Str... by Wanyue Suo, Jing Zhao

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Multilevel multiverse meta-analysis indicates lower IQ as a risk factor for physical and mental illness by Jonathan Fries, Sandra Oberleiter, Fabian A. Bodensteiner, Nikolai Fries, Jakob Pietschnig

“…Nevertheless, a meaningful effect of intelligence remained after adjusting for these variables. …”
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AI-powered diagnosis of ovarian conditions: insights from a newly introduced ultrasound dataset by Mahdi-Reza Borna, Mahdi-Reza Borna, Hanan Saadat, Mohammad Mehdi Sepehri, Hossein Torkashvand, Leila Torkashvand, Shamim Pilehvari

“…Traditional diagnostic methods, reliant on subjective ultrasound interpretation, often lead to variability in accuracy. Recent advancements in artificial intelligence (AI) and transfer learning offer promising opportunities to improve diagnostic consistency and accuracy in ovarian disease detection.MethodsWe introduced a new, publicly available dataset of ultrasound images representing three ovarian conditions: Normal, PCO, and Dominant Follicle. …”
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Improving a data mining based diagnostic support tool for rare diseases on the example of M. Fabry: Gender differences need to be taken into account. by Philipp Hahn, Werner Lechner, Rainer-Georg Siefen, Christina Lampe, Peter Nordbeck, Lorenz Grigull, Thomas Lücke

“…Since therapeutic options for Fabry disease exist, early diagnosis is important. An artificial intelligence (AI)-based diagnosis support algorithm for rare diseases has been developed in preliminary studies.…”
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