Robust lung segmentation in Chest X-ray images using modified U-Net with deeper network and residual blocks by Wiley Tam, Paul Babyn, Javad Alirezaie

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High-Performance Series-Fed Array Multiple-Input Multiple-Output Antenna for Millimeter-Wave 5G Networks by Nabeel Alsaab, Khaled Alhassoon, Fahd Alsaleem, Fahad Nasser Alsunaydih, Sayed O. Madbouly, Sherif A. Khaleel, Allam M. Ameen, Mahmoud Shaban

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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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Artificial intelligence-based non-invasive bilirubin prediction for neonatal jaundice using 1D convolutional neural network by Fatemeh Makhloughi

“…This study proposes a novel approach using 1D Convolutional Neural Networks (1DCNN) for estimating bilirubin levels from RGB, HSV, LAB, and YCbCr color channels extracted from infant images. …”
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Hybrid NARX Neural Network with Model-Based Feedback for Predictive Torsional Torque Estimation in Electric Drive with Elastic Connection by Amanuel Haftu Kahsay, Piotr Derugo, Piotr Majdański, Rafał Zawiślak

“…The approach integrates Nonlinear Autoregressive Neural Networks with Exogenous Inputs (NARX NNs) and model-based feedback. …”
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Lightweight multiscale information aggregation network for land cover land use semantic segmentation from remote sensing images by Yahia Said, Oumaima Saidani, Ali Delham Algarni, Mohammad H. Algarni, Ayman Flah

“…This paper presents a lightweight neural network designed to address these challenges by integrating dense dilated convolutions with pyramid depthwise convolutions for multiscale feature extraction. …”
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Temporal user interest modeling for online advertising using Bi-LSTM network improved by an updated version of Parrot Optimizer by Yang Yang, Lijun Zhang, Jiaquan Liu

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A Deep Sparse Capsule Network for Non-Invasive Blood Glucose Level Estimation Using a PPG Sensor by Narmatha Chellamani, Saleh Ali Albelwi, Manimurugan Shanmuganathan, Palanisamy Amirthalingam, Emad Muteb Alharbi, Hibah Qasem Salman Alatawi, Kousalya Prabahar, Jawhara Bader Aljabri, Anand Paul

“…Specifically, a Deep Sparse Capsule Network (DSCNet) model is proposed to provide accurate and robust BGL monitoring. …”
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Prediction of post-Schroth Cobb angle changes in adolescent idiopathic scoliosis patients based on neural networks and surface electromyography by Shuguang Yin, Jiangang Chen, Peng Yan

“…A systematic Schroth exercise training program was designed. sEMG data from specific muscles and Cobb angle measurements were collected. A neural network model integrating Temporal Convolutional Network (TCN), Long Short-Term Memory (LSTM) layers, and feature vectors was constructed. …”
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Development of a neural network-based risk prediction model for mild cognitive impairment in older adults with functional disability by Deyan Liu, Yuge Tian, Min Liu, Shangjian Yang

“…LASSO regression, combined with univariable and multivariable logistic regression, was employed to select feature variables for predictive modeling. Seven machine learning algorithms, including logistic regression, decision tree, random forest, support vector machine, gradient boosting decision tree, k-nearest neighbors, and neural network, were used to develop predictive models. …”
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External phantom-based validation of a deep-learning network trained for upscaling of digital low count PET data by Anja Braune, René Hosch, David Kersting, Juliane Müller, Frank Hofheinz, Ken Herrmann, Felix Nensa, Jörg Kotzerke, Robert Seifert

“…The performance of this algorithm has so far only been clinically evaluated on patient data featuring limited scan statistics and unknown actual activity concentration. …”
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Precise identification of medulloblastoma in MRI images using a convolutional neural network integrated with a self-attention mechanism by Chenhao Fang, Chao Li, Huiqing Liu, Qiang Zhou, Shuo Li, Hong Chen, Xianzhen Chen, Zhaoli Shen

“…Other single convolutional neural network models, including MobileNet, Residual Network, Densely Connected Convolutional Network, Visual Geometry Group, and Inception, were also trained. …”
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Deep Learning-Driven Beam-Steering for Dual-Polarized 28 GHz Antenna Arrays in 5G Wireless Networks by Siti Zainab M. Zainab Hamzah, Norun Farihah Abdul Malek, Sarah Yasmin Mohamad, Farah Nadia Mohd Isa, Teddy Surya Gunawan, Kuo-Sheng Chin

“…We propose a method for synthesizing the array antenna’s radiation pattern using an active element pattern-deep neural network (AEP-DNN). Beam-steering has become an attractive feature for researchers, as it enables users to move freely without affecting signal strength. …”
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A national platform for advancing self-care processes for the most common illnesses and conditions: designing, evaluating, and implementing by Khadijeh Moulaei, Somayeh salehi, Masoud Shahabian, Babak sabet, Farshid Rezaei, Adrina Habibzadeh, Mohammad Reza Afrash

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CriSALAD: Robust Visual Place Recognition Using Cross-Image Information and Optimal Transport Aggregation by Jinyi Xu, Yuhang Ming, Minyang Xu, Yaqi Fan, Yuan Zhang, Wanzeng Kong

“…While existing methods leverage neural networks to enhance performance and robustness, they often suffer from the limited representation power of local feature extractors. …”
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Bitemporal Remote Sensing Change Detection With State-Space Models by Lukun Wang, Qihang Sun, Jiaming Pei, Muhammad Attique Khan, Maryam M. Al Dabel, Yasser D. Al-Otaibi, Ali Kashif Bashir

“…In addition, a bitemporal feature fusion module is proposed to fuse bitemporal features, improving temporal–spatial feature representation. …”
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DK-SLAM: Monocular Visual SLAM with Deep Keypoint Learning, Tracking, and Loop Closing by Hao Qu, Lilian Zhang, Jun Mao, Junbo Tie, Xiaofeng He, Xiaoping Hu, Yifei Shi, Changhao Chen

“…The performance of visual SLAM in complex, real-world scenarios is often compromised by unreliable feature extraction and matching when using handcrafted features. …”
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AI-Driven Framework for Recognition of Guava Plant Diseases through Machine Learning from DSLR Camera Sensor Based High Resolution Imagery by Ahmad Almadhor, Hafiz Tayyab Rauf, Muhammad Ikram Ullah Lali, Robertas Damaševičius, Bader Alouffi, Abdullah Alharbi

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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

“…An application of an unsupervised neural network-based computer-aided diagnosis (CAD) system is reported for the detection and characterization of small indeterminate breast lesions, average size 1.1 mm, in dynamic contrast-enhanced MRI. …”
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MAMNet: Lightweight Multi-Attention Collaborative Network for Fine-Grained Cropland Extraction from Gaofen-2 Remote Sensing Imagery by Jiayong Wu, Xue Ding, Jinliang Wang, Jiya Pan

“…To address the issues of high computational complexity and boundary feature loss encountered when extracting farmland information from high-resolution remote sensing images, this study proposes an innovative CNN–Transformer hybrid network, MAMNet. …”
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