GA-AGN: A generative adversarial network and attention gated network model for enhanced lung cancer detection using chest CT scans by Shenson Joseph, Herat Joshi, Meetu Malhotra, Shazia Fathima, Madhao Wagh, Kirankumar Kulkarni, Somya Singh, Onkar Mayekar, Mehedi Hassan

“…Initially, the chest CT scan images are subjected to the pre-processing phase, where image resizing and normalization are used to preprocess the images. …”
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Evaluation of a fusion model combining deep learning models based on enhanced CT images with radiological and clinical features in distinguishing lipid-poor adrenal adenoma from me... by Shao-Cai Wang, Sheng-Nan Yin, Zi-You Wang, Ning Ding, Yi-Ding Ji, Long Jin

“…Methods A retrospective analysis was conducted on abdominal contrast-enhanced CT images and clinical data from 416 pathologically confirmed adrenal tumor patients at our hospital from July 2019 to December 2024. …”
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Auto-segmentation of cerebral cavernous malformations using a convolutional neural network by Chi-Jen Chou, Huai-Che Yang, Cheng-Chia Lee, Zhi-Huan Jiang, Ching-Jen Chen, Hsiu-Mei Wu, Chun-Fu Lin, I-Chun Lai, Syu-Jyun Peng

“…The training data included initial MRI images with target CCM regions manually annotated by neurosurgeons. …”
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Nondestructive Identification of Salmon Adulteration with Water Based on Hyperspectral Data by Tao Zhang, Biyao Wang, Pengtao Yan, Kunlun Wang, Xu Zhang, Huihui Wang, Yan Lv

“…The original hyperspectral data were processed through the principal-component analysis (PCA). …”
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An Automatic Modulation Recognition Algorithm Based on Time–Frequency Features and Deep Learning with Fading Channels by Xiaoya Zuo, Yuan Yang, Rugui Yao, Ye Fan, Lu Li

“…Subsequently, it binarizes the image and feeds it as input data to the neural network. …”
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Patterns of care for people presenting to Australian general practice with musculoskeletal complaints based on routinely collected data: protocol for an observational cohort study... by Alexandra Gorelik, Romi Haas, Ljoudmila Busija

“…Outcome Health’s POpulation Level Analysis and Reporting (POLAR) database uses de-identified electronic health records to analyse general practice data in Australia. …”
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The Importance of Clinical Data for the Diagnosis of Breast Tumours in North Afghanistan by Gerhard Stauch, Peter Fritz, Rauofi Rokai, Atiq Sediqi, Haroon Firooz, Hans Ullrich Voelker, Michael Weinhara, Joachim Mollin, Bishara Soudah, Peter Dalquen, Friedhelm Brinckmann, Jürgen Dippon

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Bayesian Spatial NBDA for Diffusion Data with Home-Base Coordinates. by Glenna F Nightingale, Kevin N Laland, William Hoppitt, Peter Nightingale

“…Network-based diffusion analysis (NBDA) is a statistical method that allows the researcher to identify and quantify a social influence on the spread of behaviour through a population. …”
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Robustness of Neural Ratio and Posterior Estimators to Distributional Shifts for Population-level Dark Matter Analysis in Strong Gravitational Lensing by Andreas Filipp, Yashar Hezaveh, Laurence Perreault-Levasseur

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Identifying fabricated networks within authorship-for-sale enterprises by Simon J. Porter, Leslie D. McIntosh

“…Fabricated papers do not just need text, images, and data however, they also require a fabricated or partially fabricated network of authors. …”
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Recognition of Visual Arabic Scripting News Ticker From Broadcast Stream by Moeen Tayyab, Ayyaz Hussain, Mohammed Ali Alshara, Shakir Khan, Reemiah Muneer Alotaibi, Abdul Rauf Baig

“…Moreover, our method is evaluated on a challenging Urdu Printed Text Images (UPTI) dataset that only provides ligature based annotations. …”
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Multi-channel spatio-temporal graph attention contrastive network for brain disease diagnosis by Chaojun Li, Kai Ma, Shengrong Li, Xiangshui Meng, Ran Wang, Daoqiang Zhang, Qi Zhu

“…Specifically, we first construct dynamic brain functional networks from fMRI data with sliding windows, and embed the structural connectivity derived from diffusion tensor imaging (DTI) to the dynamic functional connectivity graph representation to construct multi-modal brain network. …”
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Impact of JPEG compression on the metrological characteristics of industrial CT data by Steffen Kieß, Robin Trostorf, Hieu Tran, Jajnabalkya Guhathakurta, Sven Simon, Ulrich Neuschaefer-Rube

“…Handling these large amounts of data poses a considerable challenge in metrology in terms of sufficiently fast visualization, analysis and data transfer via networks (local networks or over the Internet) as well as cost- and energy-efficient archiving of TB to PB data volumes. …”
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VGGBM-Net: A Novel Pixel-Based Transfer Features Engineering for Automated Coffee Bean Diseases Classification by Muhammad Shadab Alam Hashmi, Azam Mehmood Qadri, Ali Raza, Saleem Ullah, Aseel Smerat, Changgyun Kim, Muhammad Syafrudin, Norma Latif Fitriyani

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Classification of Structural and Functional Development Stage of Cardiomyocytes Using Machine Learning Techniques by V. R. Bondarev, K. O. Ivanko, N. G. Ivanushkina

“… The study is dedicated to the problem of classification of structural and functional development stage of cardiomyocytes derived from the induced pluripotent stem cells with application of the digital image processing methods and machine learning algorithms, in particular, neural networks. …”
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Optimizing healthcare big data performance through regional computing by Tariq Alsahfi, Afzal Badshah, Omar Ibrahim Aboulola, Ali Daud

“…Abstract The healthcare sector is experiencing a digital transformation propelled by the Internet of Medical Things (IOMT), real-time patient monitoring, robotic surgery, Electronic Health Records (EHR), medical imaging, and wearable technologies. This proliferation of digital tools generates vast quantities of healthcare data. …”
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Semi-Supervised Deep Subspace Embedding for Binary Classification of Sella Turcica by Kaushlesh Singh Shakya, Azadeh Alavi, Julie Porteous, Priti Khatri, Amit Laddi, Manojkumar Jaiswal, Vinay Kumar

“…Moreover, existing semi-supervised learning (SSL) methods face key limitations such as shift invariance, inadequate feature representation, overfitting on small datasets, and a lack of generalization to unseen variations in ST morphology. Medical imaging data are often unlabeled, limiting the training of automated classification systems for ST morphology. …”
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Assessment of Bone Aging—A Comparison of Different Methods for Evaluating Bone Tissue by Paweł Kamiński, Aleksander Gali, Rafał Obuchowicz, Michał Strzelecki, Adam Piórkowski, Marcin Kociołek, Elżbieta Pociask, Joanna Kwiecień, Karolina Nurzyńska

“…Automatically selecting radiomic features for machine learning models achieves a MAE of 7.99, whereas utilizing well-known convolutional architectures on the original image results in a system efficacy of 7.96. The use of artificial intelligence in medical data analysis produces comparable outcomes; however, when dealing with a large number of descriptors, selecting the most optimal ones through statistical analysis enables the identification of the best solution quickly.…”
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Prediction of the Quality of Anxi Tieguanyin Based on Hyperspectral Detection Technology by Tao Wang, Yongkuai Chen, Yuyan Huang, Chengxu Zheng, Shuilan Liao, Liangde Xiao, Jian Zhao

“…In this study, hyperspectral imaging (HSI) technology was combined with chemometric methods to achieve the rapid determination of free amino acid and tea polyphenol contents in Tieguanyin tea. …”
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Application of Deep Learning in Forest Fire Prediction: A Systematic Review by Cesilia Mambile, Shubi Kaijage, Judith Leo

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