Artificial intelligence for prediction of atrial fibrillation in the stroke unit: a retrospective derivation validation cohort studyResearch in context by Maximilian Schoels, Laura Krumm, Alexander Nelde, Manuel C. Olma, Christian H. Nolte, Jan F. Scheitz, Markus G. Klammer, Christoph Leithner, Andreas Meisel, Franziska Scheibe, Michael Krämer, Karl Georg Haeusler, Matthias Endres, Christian Meisel

“…Several artificial intelligence models have been proposed to predict AF based on ECG in sinus rhythm, but broad implementation has been limited. …”
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Body weight and BMI variability linked to dementia risk: A meta-analysis by Sitian Fang, Lewei Guan, Huimin Jian, Xijian- Dai, Lianggeng Gong

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Leveraging Variable Frequency Drive Data for Nondestructive Testing and Predictive Maintenance in Industrial Systems by Carl Lee Tolbert

“…The current study examined an alternative approach using variable-frequency drive (VFD) data for real-time fault detection and predictive maintenance. …”
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PWM offline variable application based on UAV remote sensing 3D prescription map by Leng Han, Zhichong Wang, Miao He, Yajia Liu, Xiongkui He

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An intelligent algorithm to fast and accurately detect chaotic correlation dimension by Mengyan Shen, Miaomiao Ma, Zhicheng Su, Xuejun Zhang

“…Abstract Detecting the complexity of natural systems, such as hydrological systems, can help improve our understanding of complex interactions and feedback between variables in these systems. …”
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Master protocols in vocal biomarker development to reduce variability and advance clinical precision: a narrative review by Ayush Kalia, Micah Boyer, Guy Fagherazzi, Jean-Christophe Bélisle-Pipon, Yael Bensoussan

“…Utilizing artificial intelligence, machine learning, or traditional acoustic analysis, vocal biomarkers have shown promise in detecting and monitoring conditions such as respiratory disorders and cognitive impairments. …”
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Risk evaluation of metro tunnel shield construction based on game variable weight extension cloud theory by Xiaowen Sun, Lirong Wu, Dun Wu

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Using Lyα Absorption to Measure the Intensity and Variability of z ∼ 2.4 Ultraviolet Background Light by Laurel H. Weiss, Karl Gebhardt, Dustin Davis, Erin Mentuch Cooper, Maja Lujan Niemeyer, Mahdi Qezlou, Mahan Mirza Khanlari, Robin Ciardullo, Daniel Farrow, Eric Gawiser, Simon Gazagnes, Caryl Gronwall, Gary J. Hill, Donald P. Schneider

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Intelligent Control Valve Stiction Diagnosis Approach by Sami El-Ferik, Mustafa Al-Naser, Abrar Al-Amoudi, Abdullatif Al-Najim, Karim Asif Sattar

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Detecting label noise in longitudinal Alzheimer’s data with explainable artificial intelligence by Paolo Sorino, Angela Lombardi, Domenico Lofù, Tommaso Colafiglio, Antonio Ferrara, Fedelucio Narducci, Eugenio Di Sciascio, Tommaso Di Noia

“…This study explores the potential of explainable artificial intelligence to detect and characterize noisy labels in longitudinal datasets. …”
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Acoustic Fault Diagnosis Method for Rotating Machinery Based on Collaborative Perception Information Aggregation Guidance Network by Chaofan Li, Fan Zhang, Qichen Wang, Yufei Han, Tianrui Li, Fei Teng, Cai Yi, Yongmeng Wu

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Early detection of bloodstream infection in critically ill children using artificial intelligence by Hye-Ji Han, Kyunghoon Kim, June Dong Park

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Accuracy of artificial intelligence in caries detection: a systematic review and meta-analysis by Alexander Maniangat Luke, Nader Nabil Fouad Rezallah

“…Traditional diagnostic procedures such as eye inspection and radiography have limitations in detecting early-stage degradation. Artificial intelligence (AI) provides a viable alternative to improve diagnostic precision and effectiveness. …”
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VisGraphVar: A benchmark generator for Assessing Variability in Graph Analysis Using Large Vision-Language Models by Camilo Chacon Sartori, Christian Blum, Filippo Bistaffa

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Acute Psychological Stress Detection Using Explainable Artificial Intelligence for Automated Insulin Delivery by Mahmoud M. Abdel-Latif, Mudassir M. Rashid, Mohammad Reza Askari, Andrew Shahidehpour, Mohammad Ahmadasas, Minsun Park, Lisa Sharp, Lauretta Quinn, Ali Cinar

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Development of a Tool for Comprehensive Balance Assessment Based on Artificial Intelligence and Anomaly Detection by Márcio Fagundes Goethel, Klaus Magno Becker, Franciele Carvalho Santos Parolini, Ulysses Fernandes Ervilha, João Paulo Vilas-Boas

“…To address this gap, we introduced a novel artificial intelligence-based tool that leverages anomaly detection to provide a comprehensive assessment of balance performance across all age groups. …”
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Diagnostic accuracy of artificial intelligence for obstructive sleep apnea detection: a systematic review by Sara Haghighat, Muhammed Joghatayi, Julien Issa, Sarina Azimian, Janet Brinz, Ali Ashkan, Akhilanand Chaurasia, Zahra Rahimian, Linda Sangalli

“…The gold-standard diagnostic tool for OSA is polysomnography, which is expensive, time-consuming, and not accessible everywhere. Artificial intelligence (AI) algorithms can facilitate diagnosis by detecting patients’ signs and symptoms. …”
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Ensemble Computational Intelligent for Insomnia Sleep Stage Detection via the Sleep ECG Signal by Pragati Tripathi, M. A. Ansari, Tapan Kumar Gandhi, Rajat Mehrotra, Md Belal Bin Heyat, Faijan Akhtar, Chiagoziem C. Ukwuoma, Abdullah Y. Muaad, Yasser M. Kadah, Mugahed A. Al-Antari, Jian Ping Li

“…Therefore, the automatic insomnia diagnosis from the electrocardiogram (ECG) records is vital for timely detection and cure. In this paper, a novel hybrid artificial intelligence (AI) approach is proposed based on the power spectral density (PSD) of the heart rate variability (HRV) to detect insomnia in three classification scenarios: (1) subject-based classification scenario (normal Vs. insomnia), (2) sleep stage-based classification (REM Vs. …”
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Artificial Intelligence in Inflammatory Bowel Disease Endoscopy by Sabrina Gloria Giulia Testoni, Guglielmo Albertini Petroni, Maria Laura Annunziata, Giuseppe Dell’Anna, Michele Puricelli, Claudia Delogu, Vito Annese

“…For example, the achievement of mucosal healing has been widely demonstrated as a prognostic marker for better outcomes and a reduced risk of dysplasia and cancer; however, the accuracy of endoscopy is crucial for both this aim and the precise and reproducible evaluation of endoscopic activity and the detection of dysplasia. Artificial intelligence (AI) has drastically altered the field of GI studies and is being extensively applied to medical imaging. …”
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Efficient traffic sign recognition using YOLO for intelligent transport systems by Cong Wang, Bin Zheng, Chenxing Li

“…This study proposes an optimized YOLOv5-based framework to address challenges such as small-scale detection, environmental variability, and real-time processing constraints. …”
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