Extraction of Fetal Electrocardiogram by Combining Deep Learning and SVD-ICA-NMF Methods by Said Ziani, Yousef Farhaoui, Mohammed Moutaib

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Towards Automated Frequency Response Analysis of Power Transformers with Deep Learning by Micah Phillip, Arvind Singh, Craig J. Ramlal

“…Results revealed that networks trained using image-encoded FRA data outperformed those trained using series FRA data.…”
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Brain functional connectivity correlates of autism diagnosis and familial liability in 24-month-olds by John R Pruett Jr., Alexandre A Todorov, Zoë W Hawks, Muhamed Talovic, Tomoyuki Nishino, Steven E Petersen, Savannah Davis, Lyn Stahl, Kelly N Botteron, John N Constantino, Stephen R Dager, Jed T Elison, Annette M Estes, Alan C Evans, Guido Gerig, Jessica B Girault, Heather Hazlett, Leigh MacIntyre, Natasha Marrus, Robert C McKinstry, Juhi Pandey, Robert T Schultz, William D Shannon, Mark D Shen, Abraham Z Snyder, Martin Styner, Jason J Wolff, Lonnie Zwaigenbaum, Joseph Piven, for the IBIS Network

“…Methods fcMRI comparisons of high-familial-likelihood (HL) ASD-positive (HLP, N = 23) and ASD-negative (HLN, N = 91), and low-likelihood ASD-negative (LLN, N = 27) 24-month-olds from the Infant Brain Imaging Study (IBIS) Network were conducted, employing object oriented data analysis (OODA), support vector machine (SVM) classification, and network-level fcMRI enrichment analyses. …”
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Analytical Device and Prediction Method for Urine Component Concentrations by Zhe Wang, Jianbang Huang, Qimeng Chen, Yuanhua Yu, Xuan Yu, Yue Zhao, Yan Wang, Chunxiang Shi, Zizhao Zhao, Dachun Tang

“…To tackle the low-accuracy problem with analyzing urine component concentrations in real time, a fully automated dipstick analysis device of urine dry chemistry was designed, and a prediction method combining an image acquisition system with a whale optimization algorithm (WOA) for BP neural network optimization was proposed. …”
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Feature Recognition of Human Motion Behavior Based on Depth Sequence Analysis by Guangyong Zhao

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In-vivo high-resolution χ-separation at 7T by Jiye Kim, Minjun Kim, Sooyeon Ji, Kyeongseon Min, Hwihun Jeong, Hyeong-Geol Shin, Chungseok Oh, Robert J. Fox, Ken E. Sakaie, Mark J. Lowe, Se-Hong Oh, Sina Straub, Seong-Gi Kim, Jongho Lee

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Multi-atlas multi-modality morphometry analysis of the South Texas Alzheimer’s Disease Research Center postmortem repository by Nicolas Honnorat, Mariam Mojtabai, Karl Li, Jinqi Li, David Michael Martinez, Tanweer Rashid, Morgan Smith, Margaret E Flanagan, Elyas Fadaee, Morgan Fox Torres, Mallory Keating, Kevin Bieniek, Sudha Seshadri, Mohamad Habes

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Deep learning approach based on a patch residual for pediatric supracondylar subtle fracture detection by Qingming Ye, Zhilu Wang, Yi Lou, Yang Yang, Jue Hou, Zheng Liu, Weiguang Liu, Jiayu Li

“…However, their diagnosis can be particularly challenging due to the anatomical characteristics and imaging features of the pediatric skeleton. In recent years, convolutional neural networks (CNNs) have achieved notable success in medical image analysis, though their performance typically relies on large-scale, high-quality labeled datasets. …”
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Spatial Gap-Filling of Himawari-8 Hourly AOD Products Using Machine Learning with Model-Based AOD and Meteorological Data: A Focus on the Korean Peninsula by Youjeong Youn, Seoyeon Kim, Seung Hee Kim, Yangwon Lee

“…This study introduces a spatial gap-filling method for Himawari-8/Advanced Himawari Imager (AHI) hourly AOD data, using a Random Forest (RF) model that integrates meteorological variables and model-based AOD data. …”
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Application of machine learning in acute upper gastrointestinal bleeding: bibliometric analysis by Qun Li, Guolin Chen, Qiongjie Li, Dongna Guo

“…The study found that these papers mainly focus on three core research hotspots: deepening clinical consensus, precise analysis of medical images, and optimization of data integration and decision support systems.ConclusionsThis study summarizes the latest advancements in the application of machine learning to AUGIB research. …”
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Abrasion Resistance and Mechanism Analysis of Polyethylene Fiber-reinforced Cementitious Composite by ZI Jinjia, LI Weibin, WANG Jihong, WANG Zhiwen, LIU Yunjun, NONG Qingshun, LI Bixiong

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Small Lesions Evaluation Based on Unsupervised Cluster Analysis of Signal-Intensity Time Courses in Dynamic Breast MRI by A. Meyer-Baese, T. Schlossbauer, O. Lange, A. Wismueller

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Unresponsiveness induced by sevoflurane and propofol is associated with reduced basal forebrain cholinergic nuclei functional connectivity in humans, a pilot exploratory study by Juliana Zimmermann, Rachel Nuttall, Daniel Golkowski, Gerhard Schneider, Andreas Ranft, Rüdiger Ilg, Afra Wohlschlaeger, Christian Sorg, Marlene Tahedl

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Multimodal Deep Learning for Android Malware Classification by James Arrowsmith, Teo Susnjak, Julian Jang-Jaccard

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Brainwide Analysis of Functional Connectivity Patterns in Specific Phobia and Its Treatment by Markus Muehlhan, Judith Schäfer, Kevin Hilbert, Esther Seidl, Katja Beesdo-Baum

“…Methods: We used functional magnetic resonance imaging in combination with hypothesis-free, data-driven functional connectivity multivariate pattern analysis (fc-MVPA) to identify differences between 72 individuals with SP and a nonphobic control group (CG) (n = 82). …”
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Analysis of Heuristic Uniform Theory of Diffraction Coefficients for Electromagnetic Scattering Prediction by Diego Tami, Cássio G. Rego, Dinael Guevara, Andrés Navarro, Fernando J. S. Moreira, Jordi Giménez, Hernan G. Triana

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Exploring CycleGAN Technique for Improved Plant Disease Detection and Analysis by Ouyang Luyi

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Impaired degree centrality and effective connectivity contributed to deficits in cognition and depression in patients with temporal lobe epilepsy by Bailing Qin, Shujun Su, Xuemei Chen, Yuting Sun, Qin Zhou, Huoyou Hu, Lu Qin, Jinou Zheng

“…According to the current study, patients with TLE may have cognitive and depressive deficits as a result of abnormalities in the hub and related nodes in the default mode network and visual network. Moreover, the GCA might be a good imaging feature for the diagnosis of TLE.…”
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Toward AI-Driven Cough Sound Analysis for Respiratory Disease Diagnosis by Houda Benaliouche, Houda Hafi, Hakim Bendjenna, Zeyad Alshaikh

“…Various techniques are used to identify respiratory conditions, from diagnosis to therapy, such as Computer Tomography (CT) scans and Chest X-ray (CXR) images. However, these methods require expert radiologists for manual examination, posing time challenges. …”
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Dynamic Patch-Based Sample Generation for Pulmonary Nodule Segmentation in Low-Dose CT Scans Using 3D Residual Networks for Lung Cancer Screening by Ioannis D. Marinakis, Konstantinos Karampidis, Giorgos Papadourakis, Mostefa Kara

“…This paper presents the development and evaluation of a computer-aided diagnostic system for lung cancer screening, focusing on pulmonary nodule segmentation in low-dose CT images, by employing HighRes3DNet. HighRes3DNet is a specialized 3D convolutional neural network (CNN) architecture based on ResNet principles which uses residual connections to efficiently learn complex spatial features from 3D volumetric data. …”
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