Structural and functional connectivity coupling as an imaging marker for bone metastasis pain in lung cancer patients by Jiahui Zheng, Chengfang Wang, Xiaoyu Zhou, Yu Tang, Lin Tang, Yong Tan, Jing Zhang, Hong Yu, Jiuquan Zhang, Daihong Liu

“…In addition, the convolutional neural network (CNN) model was selected to analyze and classify three groups based on individualized networks. …”
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Development and validation of a deep learning-enhanced prediction model for the likelihood of pulmonary embolism by Yu Tian, Yu Tian, Jingjie Liu, Shan Wu, Yucong Zheng, Rongye Han, Qianhui Bao, Lei Li, Lei Li, Tao Yang

“…Our prediction model uses a convolutional neural network (CNN), enhanced with three custom-designed modules for better performance. …”
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New probabilistic methods for quantitative climate reconstructions applied to palynological data from Lake Kinneret by T. Netzel, A. Miebach, T. Litt, A. Hense

“…For the models and biome distributions used, a simple feedforward neural network provides the optimal choice of the classification problem.…”
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Nerve‐Inspired Optical Waveguide Stretchable Sensor Fusing Wireless Transmission and AI Enabling Smart Tele‐Healthcare by Tianliang Li, Qian'ao Wang, Zichun Cao, Jianglin Zhu, Nian Wang, Run Li, Wei Meng, Quan Liu, Shifan Yu, Xinqin Liao, Aiguo Song, Yuegang Tan, Zude Zhou

“…A speech recognition and human‐machine interaction system, based on sensor signal acquisition, is constructed, and the convolutional neural network algorithm is integrated for disease assessment. …”
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Automatic detection of floating instream large wood in videos using deep learning by J. Aarnink, J. Aarnink, T. Beucler, T. Beucler, M. Vuaridel, V. Ruiz-Villanueva, V. Ruiz-Villanueva

“…The approach uses a convolutional neural network to automatically detect wood. We sampled data to represent different wood transport conditions, combining 20 datasets to yield thousands of instream wood images. …”
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A Semi-Supervised Attention Model for Identifying Authentic Sneakers by Yang Yang, Nengjun Zhu, Yifeng Wu, Jian Cao, Dechuan Zhan, Hui Xiong

“…The model draws on the weighted average of the output feature representations, where the weights are determined by an additional shallow neural network. This allows the SSA model to focus on the most important images of a sneaker for use in identification. …”
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Predicting the exposure of mycophenolic acid in children with autoimmune diseases using a limited sampling strategy: A retrospective study by Ping Zheng, Ting Pan, Ya Gao, Juan Chen, Liren Li, Yan Chen, Dandan Fang, Xuechun Li, Fei Gao, Yilei Li

“…Ten algorithms, including Random Forest, XGBoost, LightGBM, Gradient Boosting Decision Tree, CatBoost, Artificial Neural Network, Grandient Boosting Machine, Transformer, Wide&Deep, and TabNet, were employed for modeling based on two, three, or four concentrations of MPA. …”
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Hydrological and hydrodynamic coupling simulation under composite underlying surfaces in urban polder areas by Cheng Chen, Binquan Li, Yang Xiao, Huihui Li, Taotao Zhang, Dong Xu, Huanghao Yu

“…The model was applied in flood forecasting and risk assessment. A BP neural network (BPNN) was employed for error correction to reduce model uncertainty in forecasting. …”
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Gaussian process latent variable models-ANN based method for automatic features selection and dimensionality reduction for control of EMG-driven systems by Maham Nayab, Asim Waris, Muhammad Jawad Khan, Dokhyl AlQahtani, Ahmed Imran, Syed Omer Gilani, Umer Hameed Shah

“…To overcome such issues, this paper proposes a novel approach that integrates feature reduction techniques with an artificial neural network (ANN) classifier to enhance the accuracy of high-dimensional EMG classification. …”
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Radiomics Features Based on MRI-ADC Maps of Patients with Breast Cancer: Relationship with Lesion Size, Features Stability, and Model Accuracy by Begumhan BAYSAL, Hakan BAYSAL, Mehmet Bilgin ESER, Mahmut Bilal DOGAN, Orhan ALIMOGLU

“…Objective: To predict breast cancer molecular subtypes with neural networks based on magnetic resonance imaging apparent diffusion coefficient (ADC) radiomics and to detect the relation of lesion size with the stability of radiomics features. …”
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Anatomy-Informed Multimodal Learning for Myocardial Infarction Prediction by Ivan-Daniel Sievering, Ortal Senouf, Thabo Mahendiran, David Nanchen, Stephane Fournier, Olivier Muller, Pascal Frossard, Emmanuel Abbe, Dorina Thanou

“…<italic>Methods:</italic> The images are analyzed by Convolutional Neural Networks (CNNs) guided by anatomical information, and the clinical data by an Artificial Neural Network (ANN). …”
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Evaluation of Short-Term Freeway Speed Prediction Based on Periodic Analysis Using Statistical Models and Machine Learning Models by Xiaoxue Yang, Yajie Zou, Jinjun Tang, Jian Liang, Muhammad Ijaz

“…., support vector machines (SVM) model, multi-layer perceptron (MLP) model, recurrent neural network (RNN) model) are developed and examined. …”
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High-Fidelity Depth Map Reconstruction System With RGB-Guided Super Resolution CNN and Cross-Calibrated Chaos LiDAR by Yu-Chun Ding, Chia-Yu Chang, Pei-Rong Li, Chao-Tsung Huang, Yung-Chen Lin, Tsung Chen, Wei-Lun Lin, Cheng-Ting Lee, Fan-Yi Lin, Yuan-Hao Huang

“…In this work, we propose a depth map reconstruction system that integrates an RGB-guided depth map super-resolution convolutional neural network (CNN) into a stand-alone Chaos LiDAR depth sensor. …”
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FTA-Net: Frequency-Temporal-Aware Network for Remote Sensing Change Detection by Taojun Zhu, Zikai Zhao, Min Xia, Junqing Huang, Liguo Weng, Kai Hu, Haifeng Lin, Wenyu Zhao

“…First, it has a two-branch Transformer-INN feature extractor using a Lite-Transformer that utilizes remote attention for low-frequency global features, and a invertible neural network that focuses on extracting high-frequency local information. …”
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MCPA: multi-scale cross perceptron attention network for 2D medical image segmentation by Liang Xu, Mingxiao Chen, Yi Cheng, Pengwu Song, Pengfei Shao, Shuwei Shen, Peng Yao, Ronald X. Xu

“…Abstract The UNet architecture, based on convolutional neural networks (CNN), has demonstrated its remarkable performance in medical image analysis. …”
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Klasifikasi Pola Pergerakan Bola Mata Menggunakan Metode Multilayer Backpropagation by Karina Amadea, Fitra A. Bachtiar, Gusti Pangestu

“…The presence of a neural network in the iris, helps humans to be able to find out the response to all changes in the body including changes in the spirit of life, character or even a person's nature. …”
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Metabolomics Biomarkers in Prediction of Sudden Infant Death Syndrome: The Role of Short Chain Fatty Acids by Maria Aslam, Omer Riaz, Jawaria Aslam, Dost Muhammad Khan, Mustafa Hameed, Muhammad Suleman, Rizwan Shahid, Turke Althobaiti, Naeem Ramzan

“…The application of ML, particularly the Artificial Neural Network (ANN) and Stacking model, demonstrated exceptional accuracy of 94% and 96.15% with a recall of 100% and 92.31%, respectively. …”
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Drug-induced autoimmune-like hepatitis: A disproportionality analysis based on the FAERS database. by Wangyu Ye, Yuan Ding, Meng Li, Zhihua Tian, Shaoli Wang, Zhen Liu

“…Positive signal drugs were identified using Proportional Reporting Ratio (PRR), Reporting Odds Ratio (ROR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM). …”
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Employing the concept of stacking ensemble learning to generate deep dream images using multiple CNN variants by Lafta Alkhazraji, Ayad R. Abbas, Abeer S. Jamil, Zahraa Saddi Kadhim, Wissam Alkhazraji, Sabah Abdulazeez Jebur, Bassam Noori Shaker, Mohammed Abdallazez Mohammed, Mohanad A. Mohammed, Basim Mohammed Al-Araji, Abdulkareem Z. Mohmmed, Wasiq Khan, Bilal Khan, Abir Jaafar Hussain

“…For model development, a series of five pre-trained Convolutional Neural Network (CNN) architectures—VGG-19, Inception v3, VGG-16, Inception-ResNet-V2, and Xception were stacked in an ensemble learning approach to create Deep Dream images whereby the upper hidden layers of the architectures were activated, and the models were trained via the Adam optimizer. …”
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Synergetic monitoring of pressure and temperature stimulations in multisensory electronic skin based on time decoupling effect by Zhiyi Gao, Ye Zhang, Zhenyu Hu, Dongdong Zhang, Shengbin Li, Huiyun Xiao, Ziyin Xiang, Dan Xu, Haifeng Zhang, Yuanzhao Wu, Yiwei Liu, Jie Shang, Runwei Li

“…More importantly, by equipping with a multilayer neural network, the evolution from tactile perception to advanced intelligent tactile cognition is demonstrated.…”
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