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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Study of the course of recurrent myocardial infarction in the acute stage within the framework the hospital register by S. Yu. Martsevich, A. V. Zagrebelnyy, O. S. Afonina, I. M. Kuzmina, Yu. V. Avdeev, N. A. Muradyan, O. M. Drapkina

“…Aim. To study the features of the course of primary and recurrent myocardial infarction and compare their prognosis in the acute stage of the disease within the framework of the hospital register of the vascular center.Material and methods. …”
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A Robust Multi-Modal Deep Learning-Based Fault Diagnosis Method for PV Systems by Shahabodin Afrasiabi, Sarah Allahmoradi, Mousa Afrasiabi, Xiaodong Liang, C. Y. Chung, Jamshid Aghaei

“…The proposed method combines residual convolutional neural networks (CNNs) and gated recurrent units (GRUs) to effectively extract both spatial and temporal features from raw PV data. …”
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Predicting trajectories of coastal area vessels with a lightweight Slice-Diff self attention by Jinxu Zhang, Jin Liu, Xiliang Zhang, Lai Wei, Zhongdai Wu, Junxiang Wang

“…Existing trajectory prediction studies predominantly employ recurrent neural network (RNN) and Transformer-based methods. …”
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Clinical Features of Visual Disturbances in Leiden Thrombophilia by E. E. Ioyleva, A. V. Zinov’eva

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Acoustic cues for person identification using cough sounds by Van-Thuan Tran, Ting-Hao You, Wei-Ho Tsai

“…It outperformed the same network and larger-capacity networks (i.e., VGG16 and ResNet50) trained with CE loss alone, which achieved accuracies around 90 %. Among the tested features, MFCCs yielded superior identification performance over spectrograms. …”
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Le corps du joueur et l’écran traversé : récurrences et circulation d’un motif. by Sonny Walbrou

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Damage detection in structural health monitoring using hybrid convolution neural network and recurrent neural network by Dung Bui-Ngoc, Hieu Nguyen-Tran, Lan Nguyen-Ngoc, Hoa Tran-Ngoc, Thanh Bui-Tien, Hung Tran-Viet

“…In this paper, a novel method of structural damage detection is proposed using a hybrid convolution neural network and recurrent neural network. A convolution neural network is used to extract deep features while recurrent neural network is trained to learn the long-term historical dependency in time series data. …”
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Damage Detection in Structural Health Monitoring using Hybrid Convolution Neural Network and Recurrent Neural Network by Thanh Bui-Tien, Dung Bui-Ngoc, Hieu Nguyen-Tran, Lan Nguyen-Ngoc, Hoa Tran-Ngoc, Hung Tran-Viet

“…In this paper, a novel method of structural damage detection is proposed using convolution neural network and recurrent neural network. A convolution neural network is used to extract deep features while recurrent neural network is trained to learn the long-term historical dependency in time series data. …”
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Inferring Travel Modes from Cellular Signaling Data Based on the Gated Recurrent Unit Neural Network by Yanchen Wang, Fei Yang, Li He, Haode Liu, Li Tan, Cheng Wang

“…However, due to data privacy issues, the empirical evaluation of the performance of different identification methods is not yet sufficient. This paper builds a travel mode identification model that utilizes the gated recurrent unit (GRU) neural network. …”
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