A novel myocarditis detection combining deep reinforcement learning and an improved differential evolution algorithm by Jing Yang, Touseef Sadiq, Jiale Xiong, Muhammad Awais, Uzair Aslam Bhatti, Roohallah Alizadehsani, Juan Manuel Gorriz

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Accessible AI Diagnostics and Lightweight Brain Tumor Detection on Medical Edge Devices by Akmalbek Abdusalomov, Sanjar Mirzakhalilov, Sabina Umirzakova, Abror Shavkatovich Buriboev, Azizjon Meliboev, Bahodir Muminov, Heung Seok Jeon

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Automotive DNN-Based Object Detection in the Presence of Lens Obstruction and Video Compression by Gabriele Baris, Boda Li, Pak Hung Chan, Carlo Alberto Avizzano, Valentina Donzella

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Enhancing needle puncture detection using high-pass filtering and diffuse reflectance by Rachael L’Orsa, Rachael L’Orsa, Rachael L’Orsa, Rachael L’Orsa, Anupam Bisht, Linhui Yu, Kartikeya Murari, Kartikeya Murari, Kartikeya Murari, Garnette R. Sutherland, Garnette R. Sutherland, David T. Westwick, Katherine J. Kuchenbecker

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Intelligent Diagnosis of Rolling Element Bearings Under Various Operating Conditions Using an Enhanced Envelope Technique and Transfer Learning by Ali Davoodabadi, Mehdi Behzad, Hesam Addin Arghand, Somaye Mohammadi, Len Gelman

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A hybrid machine learning and ied-based fault detection scheme for microgrids by Hamid Radmanesh, Abolfazl Hadadi

“…Existing methods often struggle to achieve accurate and timely fault identification, necessitating the development of an efficient fault detection framework. This paper proposes a new intelligent fault detection approach that leverages advanced signal processing techniques, including modified Variable Mode Decomposition (MVMD) for feature extraction, combined with a hybrid machine learning (ML) model. …”
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Age- and Post-Based Complex Analyses of Heart Rate Variability in Young Male Handball Players for Potential Prevention of Overload-induced Injuries by Zita Petrovszki, Olivér Czimbalmos, Vera Gal, Gabor Korosi, Edit Nagy, Rita Mikulan, Gyongyi Horvath

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Deep learning-based object detection for environmental monitoring using big data by Wenbo Lin, Tingting Li, Xiao Li

“…IntroductionRecent advances in artificial intelligence have transformed the way we analyze complex environmental data. …”
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Lab-to-Field Generalization Gap: Assessment of Transfer Learning for Bearing Fault Detection by Eleonora Iunusova, Andreas Archenti

“…The integration of Artificial Intelligence into industrial maintenance remains challenging due to the scarcity of high-quality data representing faulty conditions. …”
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A Multi-Domain Feature Fusion CNN for Myocardial Infarction Detection and Localization by Yunfan Chen, Jinxing Ye, Yuting Li, Zhe Luo, Jieqiang Luo, Xiangkui Wan

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Ecological monitoring of invasive species through deep learning-based object detection by Xinwu Ji, Yang Zhang, Jiaquan Wan, Tao Yang, Qiong Yang, Jiaqing Liao

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Emerging biomarkers for early cancer detection and diagnosis: challenges, innovations, and clinical perspectives by Sameen Zafar, Amna Hafeez, Hania Shah, Iqra Mutiullah, Arslan Ali, Khushbukhat Khan, Gabriela Figueroa-González, Octavio Daniel Reyes-Hernández, Laura Itzel Quintas-Granados, Sheila I. Peña-Corona, Lashyn N. Kiyekbayeva, Monica Butnariu, Cristina-Elena Tota, Angela Caunii, Dietrich Büsselberg, Javad Sharifi-Rad, Gerardo Leyva-Gómez

“…An extensive literature review focuses on recent studies and advancements in both traditional and emerging biomarkers, including circulating tumor DNA (ctDNA), exosomes, liquid biopsies, microRNAs (miRNAs), and immunotherapy biomarkers, which show promising potential for early cancer detection. Liquid biopsies, nanobiosensors, artificial intelligence, and next-generation sequencing (NGS) are transforming biomarker discovery and application. …”
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Unsupervised Anomaly Detection with Continuous-Time Model for Pig Farm Environmental Data by Heng Zhou, Seyeon Chung, Malik Muhammad Waqar, Muhammad Ibrahim Zain Ul Abideen, Arsalan Ahmad, Muhammad Ans Ilyas, Hyongsuk Kim, Sangcheol Kim

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Hyperspectral Target Detection Based on Prior Spectral Perception and Local Graph Fusion by Xiaobin Zhao, Jun Huang, Yunquan Gao, Qingwang Wang

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Research on Natural Language Misleading Content Detection Method Based on Attention Mechanism by Boning Liu

“…The rapid evolution of digital communication and the corresponding surge in deceptive or misleading content have underscored the critical need for reliable and domain-adaptive detection technologies. Within the scope of the Frontiers in Computer Science, which emphasizes intelligent information systems, trustworthy AI, and content safety, this study introduces a robust and generalizable method for detecting misleading content across diverse linguistic and contextual domains. …”
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Artificial intelligence model predicts M2 macrophage levels and HCC prognosis with only globally labeled pathological images by Huiyuan Tian, Yongshao Tian, Dujuan Li, Minfan Zhao, Qiankun Luo, Lingfei Kong, Tao Qin

“…Background and aimsThe levels of M2 macrophages are significantly associated with the prognosis of hepatocellular carcinoma (HCC), however, current detection methods in clinical settings remain challenging. …”
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Machine learning and artificial intelligence in type 2 diabetes prediction: a comprehensive 33-year bibliometric and literature analysis by Mahreen Kiran, Ying Xie, Nasreen Anjum, Graham Ball, Barbara Pierscionek, Duncan Russell

“…BackgroundType 2 Diabetes Mellitus (T2DM) remains a critical global health challenge, necessitating robust predictive models to enable early detection and personalized interventions. This study presents a comprehensive bibliometric and systematic review of 33 years (1991-2024) of research on machine learning (ML) and artificial intelligence (AI) applications in T2DM prediction. …”
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A Survey of Deep Anomaly Detection in Multivariate Time Series: Taxonomy, Applications, and Directions by Fengling Wang, Yiyue Jiang, Rongjie Zhang, Aimin Wei, Jingming Xie, Xiongwen Pang

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Enhancing detection of common bean diseases using Fast Gradient Sign Method–trained Vision Transformers by Upendo Mwaibale, Neema Mduma, Hudson Laizer, Bonny Mgawe

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From black box AI to XAI in neuro-oncology: a survey on MRI-based tumor detection by Asmita, Praveen Mittal

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