Synergizing vision transformer with ensemble of deep learning model for accurate kidney stone detection using CT imaging by Arwa Alzughaibi, Adwan A. Alanazi, Mohammed Alshahrani, Ines Hilali Jaghdam, Abaker A. Hassaballa

“…CT scans are one of the most extensively accessible imaging models, and they are employed for effective diagnosis. …”
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Preoperative assessment of tertiary lymphoid structures in stage I lung adenocarcinoma using CT radiomics: a multicenter retrospective cohort study by Xiaojiang Zhao, Yuhang Wang, Mengli Xue, Yun Ding, Han Zhang, Kai Wang, Jie Ren, Xin Li, Meilin Xu, Jun Lv, Zixiao Wang, Daqiang Sun

“…Tumor segmentation was achieved using an automatic virtual adversarial training segmentation algorithm based on a three-dimensional U-shape convolutional neural network (3D U-Net). Radiomic features were extracted from the tumor and peritumoral areas, with extensions of 2 mm, 4 mm, 6 mm, and 8 mm, respectively, and deep learning image features were extracted through a convolutional neural network. …”
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Using Deep Learning Techniques to Enhance Blood Cell Detection in Patients with Leukemia by Mahwish Ilyas, Muhammad Bilal, Nadia Malik, Hikmat Ullah Khan, Muhammad Ramzan, Anam Naz

“…Leukemia, a blood malignancy, is one of the most prevalent cancer types affecting both adults and children. …”
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Antifungal Activity and Cytotoxicity of Imidazole- and Morpholine-Based Lysosomotropic Detergents by Diana Hodyna, Vasyl Kovalishyn, Yurii Shulha, Olena Trokhimenko, Olesya Aksenovska, Sergiy Rogalsky, Larysa Metelytsia

“…It is known that the fungus Candida albicans is the most common causative agent of candidal infection, including the severe type. …”
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A Multi-Task Spatiotemporal Graph Neural Network for Transient Stability and State Prediction in Power Systems by Shuaibo Wang, Xinyuan Xiang, Jie Zhang, Zhuohang Liang, Shufang Li, Peilin Zhong, Jie Zeng, Chenguang Wang

“…While AI has shown great potential, most existing AI-based approaches focus on single tasks, such as either stability assessments or state prediction, limiting their practical applicability. …”
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Time–frequency ensemble network for wind turbine mechanical fault diagnosis by Haiyu Guo, Xingzheng Guo, Xiaoguang Zhang, Fanfan Lu, Chuang Liang

“…Second, the Transformer and Graph Convolutional Network (GCN) are combined to extract the time–frequency discriminative features of defects. …”
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Detection and classification of hypertensive retinopathy based on retinal image analysis using a deep learning approach by Bambang Krismono Triwijoyo, Ahmat Adil, Muhammad Zulfikri

“…Background: The issue is that most heart attacks and strokes happen unexpectedly to people who have signs of high blood pressure that are not identified in time for treatment. …”
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Ulcerative Severity Estimation Based on Advanced CNN–Transformer Hybrid Models by Boying Nie, Gaofeng Zhang

“…Experiments show that the CoAtNet model, which integrates convolutional and transformer components, improves UC assessment from endoscopic images, enhancing AI’s role in computer-aided diagnosis.…”
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GNSS–VTEC prediction based on CNN–GRU neural network model during high solar activities by T. Y. Yang, J. Y. Lu, Y. Y. Yang, Y. H. Hao, M. Wang, J. Y. Li, G. C. Wei

“…The performance of the CNN–GRU model is compared with the most used empirical models, IRI and NeQuick, and two artificial intelligence models, GRU and SVM. …”
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Enhancing Situational Awareness: Anomaly Detection Using Real-Time Video Across Multiple Domains by Rajan Singh, Amrit Pal, Shruti Mishra, Abishi Chowdhury

“…This paper proposes a novel approach to handle the complexity of dynamic real-world anomaly detection scenarios using three state of the art machine learning models: Convolutional Neural Networks (CNN), Region-based Convolutional Neural Network (R-CNN), and You Only Look Once (YOLO). …”
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A Comparative Study of Data-Driven Prognostic Approaches under Training Data Deficiency by Jinwoo Song, Seong Hee Cho, Seokgoo Kim, Jongwhoa Na, Joo-Ho Choi

“…While the data-driven approach is the most common for this purpose, they often face challenges due to insufficient training data. …”
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Dynamic graph attention network based on multi-scale frequency domain features for motion imagery decoding in hemiplegic patients by Yinan Wang, Yinan Wang, Lizhou Gong, Yang Zhao, Yewei Yu, Hanxu Liu, Xiao Yang

“…MFF-DANet employs convolutional kernels of various scales to extract feature information across multiple frequency bands, followed by a channel attention-based average pooling operation to retain the most critical frequency domain features. …”
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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

“…Cell regenerative therapy has become one of the most promising treatment options for patients with heart failure. …”
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Joint fusion of sequences and structures of drugs and targets for identifying targets based on intra and inter cross-attention mechanisms by Xin Zeng, Guang-Peng Su, Wen-Feng Du, Bei Jiang, Yi Li, Zi-Zhong Yang

“…MM-IDTarget integrates some cutting-edge deep learning techniques such as graph transformer, multi-scale convolutional neural networks (MCNN), and residual edge-weighted graph convolutional network (EW-GCN) to extract sequence and structure modal features of drugs and targets. …”
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Research on machine learning methods for detecting objects in difficult shooting conditions by Vitalii Serdechnyi, Olesia Barkovska, Andriy Kovalenko, Anton Havrashenko, Vitalii Martovytskyi

“…The goal of this research is to identify the most effective deep learning models based on convolutional neural networks for object detection tasks under challenging imaging conditions, considering the practical requirements for accuracy and processing speed. …”
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A deep fusion‐based vision transformer for breast cancer classification by Ahsan Fiaz, Basit Raza, Muhammad Faheem, Aadil Raza

“…Abstract Breast cancer is one of the most common causes of death in women in the modern world. …”
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Automatic detection of sleep spindles by neural networks algorithms by Jan Rychlík, Roman Mouček

“…The learning algorithms underwent training using meticulously annotated data from the Montreal Archive of Sleep Studies (MASS) data center. The convolutional neural network emerged as the most effective classification model, achieving an accuracy surpassing 67 %. …”
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Deep Learning Based on Facial Expression Recognition from Images to Videos by Deng Rui

“…Facial expressions, as a vital conduit for human emotional expression, are among the most observable features of machines in the field of computer vision. …”
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A Bridge Structure 3D Representation for Deep Neural Network and Its Application in Frequency Estimation by Kejian Hu, Xiaoguang Wu

“…Currently, most predictions related to bridge geometry use shallow neural networks, which limit the network’s ability to fit since the input form limits the depth of the neural network. …”
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Artificial intelligence for children with attention deficit/hyperactivity disorder: a scoping review by Bo Sun, Bo Sun, Fei Cai, Huiman Huang, Bo Li, Bing Wei

“…Most of the included articles used data sets with a size of <1,000 samples (28/52, 54%). …”
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