Constructing representative group networks from tractography: lessons from a dynamical approach by Eleanna Kritikaki, Matteo Mancini, Matteo Mancini, Diana Kyriazis, Natasha Sigala, Simon F. Farmer, Simon F. Farmer, Luc Berthouze

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Semi-supervised tissue segmentation from histopathological images with consistency regularization and uncertainty estimation by G. V. S. Sudhamsh, S. Girisha, R. Rashmi

“…Deep learning, particularly Convolutional Neural Networks (CNNs), offers the ability to automate this procedure by recognizing patterns in tissue images. …”
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ImageNomer: Description of a functional connectivity and omics analysis tool and case study identifying a race confound by Anton Orlichenko, Grant Daly, Ziyu Zhou, Anqi Liu, Hui Shen, Hong-Wen Deng, Yu-Ping Wang

“…To remedy this situation, we have developed ImageNomer, a data visualization and analysis tool that allows inspection of both subject-level and cohort-level demographic, genomic, and imaging features. …”
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“Infectious uveitis: a comprehensive systematic review of emerging trends and molecular pathogenesis using network analysis” by Muhammad Arif Asghar, Shixin Tang, Li Ping Wong, Peizeng Yang, Qinjian Zhao

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Image-Text Joint Learning for Social Images with Spatial Relation Model by Jiangfan Feng, Xuejun Fu, Yao Zhou, Yuling Zhu, Xiaobo Luo

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Integration of histopathological images and immunological analysis to predict M2 macrophage infiltration and prognosis in patients with serous ovarian cancer by Ling Zhao, Jiajia Tan, Qiuyuan Su, Yan Kuang, Yan Kuang

“…HIF were recognized by deep multiple instance learning (MIL) to predict M2 macrophage infiltration via theResNet18 network in the training set. The final model was evaluated using the internal and external validation set.ResultsUsing data acquired from the TCGA database, we applied univariate Cox analysis and determined that higher levels of M2 macrophage infiltration were associated with a poor prognosis (hazard ratio [HR]=6.8; 95% CI [confidence interval]: 1.6–28, P=0.0083). …”
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Enhanced skin cancer diagnosis: a deep feature extraction-based framework for the multi-classification of skin cancer utilizing dermoscopy images by Hadeel Alharbi, Gabriel Avelino Sampedro, Roben A. Juanatas, Se-jung Lim

“…Further, it presents the hybrid models CNN-Support Vector Machine (CNNSVM), CNN-Random Forest (CNNRF), and CNN-Logistic Regression (CNNLR), using a grid search for the best parameters. Exploratory Data Analysis (EDA) and random oversampling are performed to normalize and balance the data. …”
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A Modified Parallel NET (MPNET)-Based Deep Learning Technique for the Segmentation and Quantification of Visceral and Superficial Adipose Tissues of CT Scans by Josteve Adekanbi, Debashish Das, Nouh Elmitwally, Aliyuda Ali, Vince I. Madai, Bahadar Bhatia, John Morlese, Muhammed Afsal, Tanay Shah

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Predictive modelling employing machine learning, convolutional neural networks (CNNs), and smartphone RGB images for non-destructive biomass estimation of pearl millet (Pennisetum... by Faten Dhawi, Abdul Ghafoor, Norah Almousa, Sakinah Ali, Sara Alqanbar

“…Smartphone-based RGB imaging was used for data collection, and Shapley additive explanations (SHAP) methodology evaluated predictor importance. …”
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Multi-User Activity Recognition Using Plot Images Based on Ambiental Sensors by Anca Roxana Alexan, Alexandru Iulian Alexan, Stefan Oniga

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Exploring the potential of machine learning and magnetic resonance imaging in early stroke diagnosis: a bibliometric analysis (2004–2023) by Jian-cheng Lou, Xiao-fen Yu, Jian-jun Ying, Da-qiao Song, Wen-hua Xiong

“…This investigation covered the period from 2004 to 2023, with the data retrieval completed on December 1, 2023, in a single day.ResultsIn total, 395 articles were incorporated into the analysis. …”
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AI-Driven Integration of Deep Learning With Lung Imaging, Functional Analysis, and Blood Gas Metrics for Perioperative Hypoxemia Prediction by Kecheng Huang, Chujun Wu, Rongpeng Pi, Jieyu Fang

“… This viewpoint article explores the transformative role of artificial intelligence (AI) in predicting perioperative hypoxemia through the integration of deep learning with multimodal clinical data, including lung imaging, pulmonary function tests, and arterial blood gas (ABG) analysis. …”
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Brain tumor segmentation using deep learning: high performance with minimized MRI data by Jacky Huang, Banu Yagmurlu, Powell Molleti, Richard Lee, Abigail VanderPloeg, Humaira Noor, Rohan Bareja, Yiheng Li, Michael Iv, Haruka Itakura

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Multiscale Residual Weighted Classification Network for Human Activity Recognition in Microwave Radar by Yukun Gao, Lin Cao, Zongmin Zhao, Dongfeng Wang, Chong Fu, Yanan Guo

“…However, labeling a large number of radar datasets is difficult and time-consuming, and it is difficult for models trained on insufficient labeled data to obtain exact classification results. In this paper, we propose a multiscale residual weighted classification network with large-scale, medium-scale, and small-scale residual networks. …”
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A Unified Surrogate Framework for Data-Driven Reliability Analysis of Mechanical Systems from Low to Multi-DOF by Lun Shao, Alexandre Saidi, Abdel-Malek Zine, Mohamed Ichchou

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S2-IFNet: A spatial-semantic information fusion network integrated with boundary feature enhancement for forest land extraction from Sentinel-2 data by Junyang Xie, Mengyao Zhang, Hao Wu, Anqi Lin, Marcos Adami, Abdul Rashid Mohamed Shariff, Yahui Guo

“…To address these challenges, we propose a spatial-semantic information fusion network (S2-IFNet) integrated with boundary feature enhancement for forest land extraction from Sentinel-2 data. …”
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Development of Bimodal Emotion Recognition System Based on Skin Temperature and Heart Rate Variability Using Hybrid Neural Networks by Sayat Orynbassar, Duygun Erol Barkana, Evan Yershov, Madiyar Nurgaliyev, Ahmet Saymbetov, Batyrbek Zholamanov, Gulbakhar Dosymbetova, Ainur Kapparova, Nursultan Koshkarbay, Nurzhigit Kuttybay, Askhat Bolatbek, Kymbat Kopbay, Dinara Almen

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An ensemble method for cloud mask calculation based on data from the AHI instrument onboard the Himawari-8/9 satellite using convolutional neural networks by A.I. Andreev, S.I. Malkovsky, M.O. Kuchma, Y.A. Shamilova

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EMI-LTI: An enhanced integrated model for lung tumor identification using Gabor filter and ROI by Jayapradha J, Su-Cheng Haw, Naveen Palanichamy, Kok-Why Ng, Muskan Aneja, Ammar Taiyab

“…Data augmentation is employed on the pre-processed images using two proposed architectures, namely (1) Convolutional Neural Network (CNN) and (2) Enhanced Integrated model for Lung Tumor Identification (EIM-LTI). • In this study, comparisons are made on non-pre-processed data, Haar and Gabor filters in CNN and the EIM-LTI models. …”
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Point Defect Detection and Classification in MoS₂ Scanning Tunneling Microscopy Images: A Deep Learning Approach by Shiru Wu, Guoyang Chen, Si Shen, Jiaxu Yan

“…These results show the potential of combining data-driven image analysis with physics-based modeling to accelerate defect characterization in 2D materials.…”
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