Deep learning based analysis of G3BP1 protein expression to predict the prognosis of nasopharyngeal carcinoma. by Linshan Zhou, Mu Yang, Jiadi Luo, Hongjing Zang, Songqing Fan, Yuting Zhan

“…<h4>Results</h4>The G3BP1 molecular marker scoring model was successfully established utilizing deep learning methodologies, with a calculated threshold staining scores of 1.5. …”
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Integrating Data Mining, Deep Learning, and Gene Ontology Analysis for Gene Expression-Based Disease Diagnosis Systems by Sergii Babichev, Igor Liakh, Jiri Skvor

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A hybrid deep learning air pollution prediction approach based on neighborhood selection and spatio-temporal attention by Gang Chen, Shen Chen, Dong Li, Cai Chen

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Deep learning in gonarthrosis classification: a comparative study of model architectures and single vs. multi-model methods by Sahika Betul Yayli, Kutay Kılıç, Salih Beyaz

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Accuracy of Deep Learning Algorithms for the Diagnosis of Retinopathy of Prematurity by Fundus Images: A Systematic Review and Meta-Analysis by Jingjing Zhang, Yangyang Liu, Toshiharu Mitsuhashi, Toshihiko Matsuo

“…Retinopathy of prematurity (ROP) occurs in preterm infants and may contribute to blindness. Deep learning (DL) models have been used for ophthalmologic diagnoses. …”
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ThyroNet-X4 genesis: an advanced deep learning model for auxiliary diagnosis of thyroid nodules’ malignancy by Xiaoxue Wang, Yupeng Niu, Hongli Liu, Fa Tian, Qiang Zhang, Yimeng Wang, Yeju Wang, Yijia Li

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A Hybrid Approach for Sports Activity Recognition Using Key Body Descriptors and Hybrid Deep Learning Classifier by Muhammad Tayyab, Sulaiman Abdullah Alateyah, Mohammed Alnusayri, Mohammed Alatiyyah, Dina Abdulaziz AlHammadi, Ahmad Jalal, Hui Liu

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Nanomodification analysis of pore structure in GO-enhanced CWRB based on metal intrusion and BSE imaging with deep learning by Jiajian Yu, Yi Gong, Yuan Gao, Hao Sui, Xiaoli Xu, Yanming Liu

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Research on Mental Health Monitoring Scheme of Migrant Children Based on Convolutional Neural Network Based on Deep Learning by Guangyan Yang

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Deep Learning-Assisted Short-Term Power Load Forecasting Using Deep Convolutional LSTM and Stacked GRU by Fath U Min Ullah, Amin Ullah, Noman Khan, Mi Young Lee, Seungmin Rho, Sung Wook Baik

“…Stand by this, we propose an intelligent deep learning-based PLF method where at first the data collected from the house through meters are fed into the pre-assessment step. …”
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Author Correction: AIVariant: a deep learning-based somatic variant detector for highly contaminated tumor samples by Hyeonseong Jeon, Junhak Ahn, Byunggook Na, Soona Hong, Lee Sael, Sun Kim, Sungroh Yoon, Daehyun Baek

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Classification of Buried Objects From Ground Penetrating Radar Images by Using Second-Order Deep Learning Models by Douba Jafuno, Ammar Mian, Guillaume Ginolhac, Nickolas Stelzenmuller

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An approach for accurate identification and monitoring of species in mangrove forests based on multi-source spectral data and deep learning by Monterrubio-Martínez Erandi, Trujillo-Acatitla Rubicel, Tuxpan-Vargas José, Moreno-Casasola Patricia

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Author Correction: Synthetic augmentation of cancer cell line multi-omic datasets using unsupervised deep learning by Zhaoxiang Cai, Sofia Apolinário, Ana R. Baião, Clare Pacini, Miguel D. Sousa, Susana Vinga, Roger R. Reddel, Phillip J. Robinson, Mathew J. Garnett, Qing Zhong, Emanuel Gonçalves

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Enhanced early prediction of Li-ion battery degradation using multicycle features and an ensemble deep learning model by Meilia Safitri, Teguh Bharata Adji, Adha Imam Cahyadi

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FE-YOLO: An Efficient Deep Learning Model Based on Feature-Enhanced YOLOv7 for Microalgae Identification and Detection by Gege Ding, Yuhang Shi, Zhenquan Liu, Yanjuan Wang, Zhixuan Yao, Dan Zhou, Xuexiu Zhu, Yiqin Li

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Forecasting basal area increment in forest ecosystems using deep learning: A multi-species analysis in the Himalayas by P. Casas-Gómez, J.F. Torres, J.C. Linares, A. Troncoso, F. Martínez-Álvarez

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Deep Learning Model for CS-Based Signal Recovery for IRS-Assisted Near-Field THz MIMO System by Vaishali Sharma, Prakhar Keshari, Sanjeev Sharma, Kuntal Deka, Ondrej Krejcar, Vimal Bhatia

“…This method introduces an IRS signal-matched (IRSSM) measurement matrix with beam squint for capturing the transmitted signal at a sub-Nyquist rate, taking advantage of the sparsity in the signal and THz channels, and signal recovery using the deep learning (DL) model. Simulation results for symbol error rate (SER) and normalized mean square error (NMSE) performance indicate that the proposed DL-based receiver outperforms conventional recovery algorithms based on orthogonal matching pursuit (OMP) CS-recovery and dictionary-shrinkage estimation (DSE).…”
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A multi-modal deep learning model for prediction of Ki-67 for meningiomas using pretreatment MR images by Chaoyue Chen, Yanjie Zhao, Linrui Cai, Haoze Jiang, Yuen Teng, Yang Zhang, Shuangyi Zhang, Junkai Zheng, Fumin Zhao, Zhouyang Huang, Xiaolong Xu, Xin Zan, Jianfeng Xu, Lei Zhang, Jianguo Xu

“…Abstract This study developed and validated a deep learning network using baseline magnetic resonance imaging (MRI) to predict Ki-67 status in meningioma patients. …”
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Comparing Deep Learning models for mapping rice cultivation area in Bhutan using high-resolution satellite imagery by Biplov Bhandari, Timothy Mayer

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