Discussion of a Simple Method to Generate Descriptive Images Using Predictive ResNet Model Weights and Feature Maps for Recurrent Cervix Cancer by Destie Provenzano, Jeffrey Wang, Sharad Goyal, Yuan James Rao

“…Simulated images were generated as follows: [A] a ResNet model was trained to identify recurrent cervix cancer; [B] a model was evaluated on T2W MRI data for subjects to obtain corresponding feature maps; [C] most important feature maps were determined for each image; [D] feature maps were combined across all images to generate a simulated image; [E] the final image was reviewed by a radiation oncologist and an initial algorithm to identify the likelihood of recurrence. …”
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A siamese neural network model for phase identification in distribution networks by Dong Liu, Juan S. Giraldo, Peter Palensky, Pedro P. Vergara

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A multi-scale temporal feature fusion framework for sheep voiceprint recognition by Xipeng Wang, Delong Wang, Weijiao Dai, Cheng Zhang, Yudongchen Liang, Yong Zhou, Juan Yao, Fang Tian

“…The model uses the feature pyramid network (FPN) structure and a one-dimensional convolutional block attention module (1D-CBAM) for feature fusion to enhance the classification ability of the model. …”
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Application of attention mechanism-based LSTM neural network in stratigraphy identification by Cunde Jia, Xiangdong Kong, Minghui Wang, Zhuowei Yu, Haipeng Li, Yunhong Jiang, Jianliang Hu, Chao Ai

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BGATT-GR: accurate identification of glucocorticoid receptor antagonists based on data augmentation combined with BiGRU-attention by Watshara Shoombuatong, Pakpoom Mookdarsanit, Nalini Schaduangrat, Lawankorn Mookdarsanit

“…Therefore, this study proposes an innovative deep learning-based hybrid framework (termed BGATT-GR) that leverages a data augmentation method, a bidirectional gated recurrent unit (BiGRU), and a self-attention mechanism (ATT) to attain more accurate identification of GR antagonists. …”
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Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease by Hsin-Yueh Liang, Hsin-Yueh Liang, Kai-Cheng Hsu, Kai-Cheng Hsu, Kai-Cheng Hsu, Shang-Yu Chien, Chen-Yu Yeh, Ting-Hsuan Sun, Meng-Hsuan Liu, Kee Koon Ng

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Robust confinement state classification with uncertainty quantification through ensembled data-driven methods by Yoeri Poels, Cristina Venturini, Alessandro Pau, Olivier Sauter, Vlado Menkovski, the TCV Team, the WPTE Team

“…We propose ensembling data-driven methods on two axes: model formulations and feature sets. The former considers a dynamic formulation based on a recurrent Fourier neural operator-architecture and a static formulation based on gradient-boosted decision trees. …”
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Propaganda as a Category in Forensic Text Analysis by Anatolii N. Baranov, Pavel B. Parshin

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Triple-negative breast cancer: Pattern of recurrence and survival outcomes by Shyny Reddy Chintalapani, Stalin Bala, Meher Lakshmi Konatam, Sadashivudu Gundeti, Siva Prasad Kuruva, Monalisa Hui

“…This warrants further studies on intensification of chemotherapy and identification and development of targeted therapy aimed at decreasing recurrences and improving survival in this patient population.…”
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A 19-year-old Patient with Recurrent Pruritus and Jaundice by K. S. Nezhdanov, E. N. Shirokova, Yu. O. Shulpekova, A. S. Ostrovskaya, M. S. Zharkova, V. T. Ivashkin

“…Аim: to highlight the importance of broad differential diagnosis and possibility of conversion of benign recurrent intrahepatic cholestasis type 2 into more aggressive clinical phenotype.Key points. …”
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A deep learning model for prediction of lysine crotonylation sites by fusing multi-features based on multi-head self-attention mechanism by Yunyun Liang, Minwei Li

“…Multiple features are extracted from natural language processing features and hand-crafted features, where natural language processing features include token embedding and positional embedding encoded by transformer, and hand-crafted features include one-hot, amino acid index and position-weighted amino acid composition, and encoded by bidirectional long short-term memory network. …”
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Recurrent Wunderlich syndrome in systemic lupus erythematosus: a case report by Yingzi Zhu, Lingli Dong

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Advanced Prediction of Recurrent Fragility Fractures Using Large Language Models by Mohammad Alshraideh, Arafat Al-Dhaqm, Ahmad Alshammari, Abedalrahman Alshraideh, Bahaaldeen Alshraideh, Bayan Mohamed Al-Fayoumi, Maged Nasser

“…The detailed feature importance analysis showed that age and T-score have the highest important values for fracture recurrence prediction, followed by physical activity and glucocorticoid treatment. …”
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Heartbeat Stars Recognition Based on Recurrent Neural Networks: Method and Validation by Min-Yu Li, Sheng-Bang Qian, Li-Ying Zhu, Wen-Ping Liao, Lin-Feng Chang, Er-Gang Zhao, Xiang-Dong Shi, Fu-Xing Li, Qi-Bin Sun, Ping Li

“…Finally, these harmonics are normalized as feature vectors of the light curve. A training data set of synthetic light curves is constructed using ELLC, and their features are fed into recurrent neural networks (RNNs) for supervised learning, with the expected output being the eccentricity of these light curves. …”
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Genetic and oncogenic features of RASGRF fusions by Sreya Das, Daniel S. Lenchner, Ellen Jaeger, Lisa Hunihan, Dana F. DeSantis, Stamatina Fragkogianni, Karyn Ronski, Frederick H. Wilson

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Spatio-temporal characteristics and multivariate recurrence period of agricultural drought in Northwestern China by Kai Feng, Shile Wang, Yingying Wang, Yanbin Li, Tianliang Jiang, Shengzhi Huang, Fei Wang, Xiaoling Su, Zezhong Zhang

“…The evolution of drought and its recurrence period feature are important for drought mitigation and risk management. …”
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Fault Prediction of Bearing Based on Dual Dimensional Perception and Composite Gated Recurrent Network by Wang Weiping, Xue Shibei

“…After fusion and feature principal component extraction of the aforementioned two-dimensional data, the proposed composite gated recurrent network model with algorithm level attention enhancement is used for degradation state fitting identification research. …”
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A predictive model for calculating the likelihood of recurrent uterine fibroids after surgical intervention by V. B. Tskhay, S. Zh. Badmaeva, A. N. Narkevich, I. I. Tskhay, A. V. Mikhaylova

“…Our original model allows the identification of the most significant predictors of recurrent uterine fibroids and might be proposed as a useful tool for clinical practice.…”
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Identifying and Forecasting Recurrently Emerging Stock Trend Structures via Rising Visibility Graphs by Zhen Zeng, Yu Chen

“…This approach produces graph representations that capture direction-sensitive market dynamics and facilitate the extraction of meaningful topological features from price data. By applying the WL kernel, RVGWL quantifies structural similarities between graph-transformed time series, enabling the identification of structurally similar preceding patterns and the probabilistic forecasting of their subsequent trajectories based on nine canonical trend templates. …”
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Surrogate modeling of passive microwave circuits using recurrent neural networks and domain confinement by Kaustab C. Sahu, Slawomir Koziel, Anna Pietrenko-Dabrowska

“…Its main ingredient is a recurrent neural network (RNN) with the main architectural components being bidirectional Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) layers. …”
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