An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing by Morteza Ebrahimpour, Mehdi Khashei

“…The classification literature indicates that numerous classifiers with different characteristics have been developed and frequently applied across a wide range of medical diagnostic processes. …”
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The Influence of Viewing Geometry on Hyperspectral-Based Soil Property Retrieval by Yucheng Gao, Lixia Ma, Zhongqi Zhang, Xianzhang Pan, Ziran Yuan, Changkun Wang, Dongsheng Yu

“…In this study, bidirectional reflectance factors (BRFs) were collected at 48 different viewing angles for 154 soil samples with varying SOM contents and PSDs. …”
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Novel Approaches for the Early Detection of Glaucoma Using Artificial Intelligence by Marco Zeppieri, Lorenzo Gardini, Carola Culiersi, Luigi Fontana, Mutali Musa, Fabiana D’Esposito, Pier Luigi Surico, Caterina Gagliano, Francesco Saverio Sorrentino

“…Aims: The purpose of this study is to examine the current uses of AI in the early diagnosis, treatment, and detection of glaucoma while highlighting the advantages and drawbacks of different AI models and algorithms. In addition, it aims to determine how AI technologies might transform glaucoma treatment and suggest future lines of inquiry for this area of study. …”
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Enhancing Autism Spectrum Disorder Classification with Lightweight Quantized CNNs and Federated Learning on ABIDE-1 Dataset by Simran Gupta, Md. Rahad Islam Bhuiyan, Sadia Sultana Chowa, Sidratul Montaha, Rashik Rahman, Sk. Tanzir Mehedi, Ziaur Rahman

“…We developed an automated system leveraging the ABIDE-1 dataset and a novel lightweight quantized one-dimensional (1D) Convolutional Neural Network (Q-CNN) model to analyze fMRI data. …”
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Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach by Ajan Subramanian, Rui Cao, Emad Kasaeyan Naeini, Seyed Amir Hossein Aqajari, Thomas D Hughes, Michael-David Calderon, Kai Zheng, Nikil Dutt, Pasi Liljeberg, Sanna Salanterä, Ariana M Nelson, Amir M Rahmani

“…Data preprocessing involved noise filtering, feature extraction, and combining handcrafted and automatic features through convolutional and long-short-term memory autoencoders. …”
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Segmentation and particle size analysis of coal particles based on ISUNet by Deqiang CHENG, Rui ZHANG, Tongxi XIE, Jingjing LIU, Lijuan ZHENG, Qiqi KOU, He JIANG

“…The U-shaped network based on convolutional neural network architecture focus too much on local information, neglecting the importance of global information, which can lead to over-segmentation. …”
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Advancing Diabetic Retinopathy Screening: A Systematic Review of Artificial Intelligence and Optical Coherence Tomography Angiography Innovations by Alireza Hayati, Mohammad Reza Abdol Homayuni, Reza Sadeghi, Hassan Asadigandomani, Mohammad Dashtkoohi, Sajad Eslami, Mohammad Soleimani

“…Concurrently, advancements in artificial intelligence (AI), particularly deep learning (DL) architectures such as convolutional neural networks (CNNs), attention-based models, and Vision Transformers (ViTs), have revolutionized image analysis. …”
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Development of Artificial Intelligent-Based Methodology to Prepare Input for Estimating Vehicle Emissions by Elif Yavuz, Alihan Öztürk, Nedime Gaye Nur Balkanlı, Şeref Naci Engin, S. Levent Kuzu

“…Machine learning has significantly advanced traffic surveillance and management, with YOLO (You Only Look Once) being a prominent Convolutional Neural Network (CNN) algorithm for vehicle detection. …”
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The Essential Role of Monte Carlo Simulations for Lung Dosimetry in Liver Radioembolization—Part B: ¹⁶⁶Ho Microspheres by Edoardo d’Andrea, Andrea Politano, Bartolomeo Cassano, Nico Lanconelli, Marta Cremonesi, Vincenzo Patera, Massimiliano Pacilio

“…Significant underestimations in the mean absorbed dose (AD) were observed, with relative differences with respect to the reference (MC) of −64% for MIRD, −93% for kST, −56% for kST<i>_L</i>, −76% for kLT, −68% for kLT₂₂₁, and −60% for kLT<i>_L</i>. …”
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A Spatial–Frequency Combined Transformer for Cloud Removal of Optical Remote Sensing Images by Fulian Zhao, Chenlong Ding, Xin Li, Runliang Xia, Caifeng Wu, Xin Lyu

“…FreSA leverages fast Fourier transform to convert features into the frequency domain, using frequency differences between object and cloud regions to achieve precise cloud detection and fine-grained removal. …”
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Biological heart and brain ageing in subjects with cardiovascular diseases by Elizabeth Mcavoy, Elizabeth Mcavoy, Elizabeth Mcavoy, Matthias Wilms, Matthias Wilms, Matthias Wilms, Matthias Wilms, Matthias Wilms, Nils D. Forkert, Nils D. Forkert, Nils D. Forkert, Nils D. Forkert

“…However, it remains unclear to what extent different cardiovascular diseases affect brain health quantitatively across subjects and if that is associated with the extent the heart is affected by a disease. …”
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An Adaptive CNN-Based Approach for Improving SWOT-Derived Sea-Level Observations Using Drifter Velocities by Sarah Asdar, Bruno Buongiorno Nardelli

“…To address these limitations, we developed an adaptive convolutional neural network (CNN)-based filtering technique that refines SWOT-derived sea-level observations. …”
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Enhancing Traffic Accident Severity Prediction Using ResNet and SHAP for Interpretability by Ilyass Benfaress, Afaf Bouhoute, Ahmed Zinedine

“…Methods: A comparative analysis was performed with other Deep Learning (DL) architectures, including Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), Darknet, and Extreme Inception (Xception), showing superior performance of the proposed Resnet. …”
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A Novel Swin-Transformer with Multi-Source Information Fusion for Online Cross-Domain Bearing RUL Prediction by Zaimi Xie, Chunmei Mo, Baozhu Jia

“…The method uses a Bidirectional Long Short-Term Memory (Bi-LSTM) network to capture temporal features, which are transformed into 2D images using Gramian Angular Fields (GAF) for spatial feature extraction by a 2D Convolutional Neural Network (CNN). A self-attention mechanism further integrates multi-source features, while an adversarial Multi-Kernel Maximum Mean Discrepancy (MK-MMD) combined with a relational network mitigates feature distribution differences across domains. …”
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Advancing the application of the analytical renal pathology system in allograft IgA nephropathy patients by Xumeng Liu, Huiwen Fang, Dongmei Liang, Qunjuan Lei, Jiaping Wang, Feng Xu, Shaoshan Liang, Dandan Liang, Fan Yang, Heng Li, Jianghua Chen, Yuan Ni, Guotong Xie, Caihong Zeng

“…Background The analytical renal pathology system (ARPS) based on convolutional neural networks has been used successfully in native IgA nephropathy (IgAN) patients. …”
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Myoelectric signal and machine learning computing in gait pattern recognition for flat fall prediction by Shuo Zhang, Biao Chen, Chaoyang Chen, Maximillian Hovorka, Jin Qi, Jie Hu, Gui Yin, Marie Acosta, Ruby Bautista, Hussein F. Darwiche, Bryan E. Little, Carlos Palacio, John Hovorka

“…Four basic ML algorithms including support vector machine (SVM), K-nearest neighbor (kNN), decision tree (DT), and naive Bayes (NB), and five deep learning models including convolutional neural network (CNN), long-short term memory (LSTM), bidirectional long short-term memory (BiLSTM), and CNN-BiLSTM were used to process the EMG signals recorded under different gaits. …”
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Mul-material decomposition method for sandstone spectral CT images based on I-MultiEncFusion-Net by Yanfang Wu, Yanfang Wu, Yanfang Wu, Ran Zhang, Ran Zhang, Ran Zhang, Huihua Kong, Huihua Kong, Huihua Kong, Ping Chen, Ping Chen, Ping Chen, Yu Zou

“…However, traditional convolutional neural networks (CNNs) demonstrate limited effectiveness in capturing non-local features. …”
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Traditional Chinese medicine diagnostic prediction model for holistic syndrome differentiation based on deep learning by Zhe Chen, Dong Zhang, Chunxiang Liu, Hui Wang, Xinyao Jin, Fengwen Yang, Junhua Zhang

“…Symptom feature visualization demonstrated that the TCM-BERT-CNN model can effectively identify the correlation and characteristics of symptoms in different syndromes with a strong correlation, which conforms to the diagnostic characteristics of TCM syndromes. …”
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GAN-enhanced deep learning for improved Alzheimer's disease classification and longitudinal brain change analysis by Purushottam Pandey, Surbhi Bhatia Khan, Surbhi Bhatia Khan, Surbhi Bhatia Khan, Jyoti Pruthi, Eid Albalawi, Ali Algarni, Ahlam Almusharraf

“…These brain simulation models help visualize and predict how AD may evolve in different regions of the brain, enhancing both diagnosis and treatment planning.…”
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A Camera-Embedded Self-Adaptable Finger With Multi-Modal Sensing Capabilities for Robotic Manipulation by Muhammad Usman Khalid, Hafiz Muizz Ahmed Sethi, Nirmal Kumar Ravikumar, Halar Haleem, Alessandro Seitone, Mattia Frascio, Perla Maiolino, Matteo Zoppi

“…We combined two algorithms: an optical flow-based method for reliably detecting slip events and a Convolutional Neural Network (CNN) for force, displacement estimation, and position classification. …”
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