Pyramidal attention-based T network for brain tumor classification: a comprehensive analysis of transfer learning approaches for clinically reliable and reliable AI hybrid approach... by Tathagat Banerjee, Prachi Chhabra, Manoj Kumar, Abhay Kumar, Kumar Abhishek, Mohd. Asif Shah

“…Although current state-of-the-art deep learning methods have achieved remarkable progress, there is still a gap in the representation learning of tumor-specific spatial characteristics and the robustness of the classification model on heterogeneous data. In this paper, we introduce a novel Pyramidal Attention-Based bi-partitioned T Network (PABT-Net) that combines the hierarchical pyramidal attention mechanism and T-block based bi-partitioned feature extraction, and a self-convolutional dilated neural classifier as the final task. …”
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Facilitating real-time LED-based photoacoustic imaging with DenP2P: An optimized conditional generative adversarial deep learning solution by Avijit Paul, Srivalleesha Mallidi

“…Photoacoustic imaging (PAI) benefits from the optical absorption contrast of the tissue while achieving greater depth information with ultrasound resolution than the other optical imaging platforms. …”
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Biobanking for discovery of novel cardiovascular biomarkers using imaging-quantified disease burden: protocol for the longitudinal, prospective, BioHEART-CT cohort study by Clara Chow, Leonard Kritharides, Sanjay Patel, Katharine A Kott, Stephen T Vernon, Thomas Hansen, Christine Yu, Kristen J Bubb, Sean Coffey, David Sullivan, Jean Yang, John O'Sullivan, James Chong, David S Celermajer, Stuart M Grieve, Gemma A Figtree

“…After informed consent, patient data, blood samples and CTCA imaging data are recorded. …”
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Artificial intelligence in the interpretation of upper extremity trauma radiographs: a systematic review and meta-analysis by Matthew Mellon, BSc, Joshua Dworsky-Fried, BHSc, Preksha Rathod, MD, Darshil Shah, MBBS, Moin Khan, MD, James Yan, MD

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(H-DIR)²: A Scalable Entropy-Based Framework for Anomaly Detection and Cybersecurity in Cloud IoT Data Centers by Davide Tosi, Roberto Pazzi

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Assessing dynamic brain activity during verbal associative learning using MEG/fMRI co-processing by Sangeeta Nair, Jerzy P. Szaflarski, Yingying Wang, Diana Pizarro, Jeffrey F. Killen, Jane B. Allendorfer

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EarlyExodus: Leveraging early exits to mitigate backdoor vulnerability in deep learning by Salmane Douch, M. Riduan Abid, Khalid Zine-Dine, Driss Bouzidi, Fatima Ezzahra El Aidos, Driss Benhaddou

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3-D fracture network reconstruction and quantitative fractal analysis of subsurface rock fractures via integrated CT scanning and box-counting dimension methodology by Hongjian Wu, Xiangwei Kong, Xing Chen, Dianwei Guan

“…These innovations collectively advance fracture network analysis from qualitative description to true multi-parameter predictive modeling, addressing critical gaps in current practice.…”
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Switch to mania after acute antidepressant treatment for bipolar depression: a systematic review and network meta-analysis of randomised controlled trialsResearch in context by Vincenzo Oliva, Michele De Prisco, Enrico La Spina, Sofia Paolucci, Giovanna Fico, Gerard Anmella, Diego Hidalgo-Mazzei, Andrea Murru, Maurizio Pompili, Michele Fornaro, Marco Solmi, Ayşegül Yildiz, Stefan Leucht, Eduard Vieta, Joaquim Radua

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Analysis of spatio-temporal fungal growth dynamics under different environmental conditions by Liselotte De Ligne, Guillermo Vidal-Diez de Ulzurrun, Jan M. Baetens, Jan Van den Bulcke, Joris Van Acker, Bernard De Baets

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DESIGN OF AN IMPROVED MODEL FOR CARDIOVASCULAR DISEASE DETECTION USING DEEP CANONICAL CORRELATION ANALYSIS AND BIOINSPIRED OPTIMIZATION by Prakash Chandra Sahoo, Binod Kumar Pattanayak, Rajani Kanta Mohanty, Ayasa Kanta Mohanty

“…On this, we propose a novel framework for the detection of cardiovascular diseases and presiding analysis through multimodal data fusion, optimized neural networks, and explainable AI techniques. …”
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Can YOLO Detect Retinal Pathologies? A Step Towards Automated OCT Analysis by Adriana-Ioana Ardelean, Eugen-Richard Ardelean, Anca Marginean

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High-accuracy prediction of mutations in nine genes in lung adenocarcinoma via two-stage multi-instance learning on large-scale whole-slide images by Lingyu Zhao, Na Zhao, Ruiqi Zhong, Yiru Niu, Ziyi Chang, Peng Su, Zhihui Wang, Lifang Cui, Bei Wang, Huang Chen, Xiaowen Wang, Xiangbing Kong, Baolin Du, Fei Ren, Dingrong Zhong

“…Methods We collected 2,221 slides from 1999 patients diagnosed with lung adenocarcinoma. The data include whole-slide images data as well as information on gene mutations in EGFR, KRAS, ALK, HER2, and other rare genes (ROS1, RET, BRAF, PIK3CA, NRAS), and related clinical information. …”
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A novel sub-network level ensemble deep neural network with a regularized loss function to improve prediction performance by Jalil Toosifar, Yahya Forghani, Seyyed Abed Hosseini, Nasser Shoeibi

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MCAUnet: a deep learning framework for automated quantification of body composition in liver cirrhosis patients by Jiening Wang, Shuqi Xia, Jie Zhang, Xinyi Wang, Cai Zhao, Wen Zheng

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Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study. by Md Nasir, Yixi Xu, Kyle Hasenstab, Alekhya Yechoor, Rahul Dodhia, William B Weeks, Juan Lavista Ferres, Guilherme Moura Cunha

“…After liver segmentation and registration, a deep neural network (DNN) with 3D U-Net architecture was trained using CECT images as single channel input and the concurrent MRI-PDFF images as single channel output. …”
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Long-Term Monitoring of Coastal Water Quality Using Sentinel-2 Satellite Images and Google Earth Engine: The Case Study Izmir and Erdek Bays by O. Y. Altuntas, M. Saygi, I. Colkesen

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Dynamic changes in brain function during sleep deprivation: Increased occurrence of non-stationary states indicates the extent of cognitive impairment by Ziliang Xu, Chaozong Ma, Chen Wang, Fan Guo, Minwen Zheng, Peng Fang, Yuanqiang Zhu

“…Methods: The data from 32 subjects, encompassing resting state and psychomotor vigilance task (PVT) functional magnetic resonance imaging data collected at five different timepoints (22:00, 00:00, 02:00, 04:00 and 06:00) during a whole night were acquired. …”
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Land-Unet: A deep learning network for precise segmentation and identification of non-structured land use types in rural areas for green urban space analysis by Yan Zhao, Junru Xie, Huiru Zhu, Taige Luo, Yao Xiong, Chenyang Fan, Haoxiang Xia, Yuheng Chen, Fuquan Zhang

“…With the development of artificial intelligence technology, many downstream applications based on intelligent urban–rural semantic analysis have emerged. Scholars have made significant progress in the intelligent analysis of urban imagery, but exploration of unstructured rural remote sensing data has been limited. …”
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Frequency Domain-Based Super Resolution Using Two-Dimensional Structure Consistency for Ultra-High-Resolution Display by Yu Lim Seo, Suk-Ju Kang, Yeon-Kug Moon

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