A deep learning approach for classifying and predicting children's nutritional status in Ethiopia using LSTM-FC neural networks by Getnet Bogale Begashaw, Temesgen Zewotir, Haile Mekonnen Fenta

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Deep Learning-Based Glucose Prediction Models: A Guide for Practitioners and a Curated Dataset for Improved Diabetes Management by Saul Langarica, Diego de la Vega, Nawel Cariman, Martin Miranda, David C. Andrade, Felipe Nunez, Maria Rodriguez-Fernandez

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PharmacoNER Tagger: a deep learning-based tool for automatically finding chemicals and drugs in Spanish medical texts by Jordi Armengol-Estapé, Felipe Soares, Montserrat Marimon, Martin Krallinger

“…In the recent years, the field of natural language processing has mainly pivoted to deep learning and state-of-the-art results for most tasks involving natural language are usually obtained with artificial neural networks. …”
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Clinical feasibility of deep learning-driven magnetic resonance angiography collateral map in acute anterior circulation ischemic stroke by Ye Jin Jeon, Hong Gee Roh, Sumin Jung, Hyun Yang, Hee Jong Ki, Jeong Jin Park, Taek-Jun Lee, Na Il Shin, Ji Sung Lee, Jin Tae Kwak, Hyun Jeong Kim

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Diagnosis and prognosis of melanoma from dermoscopy images using machine learning and deep learning: a systematic literature review by Hoda Naseri, Ali A. Safaei

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Energy Use and Demand Prediction Using Time-Series Deep Learning Forecasting Techniques: Application for a University Campus by Bivin Pradeep, Parag Kulkarni, Farman Ullah, Abderrahmane Lakas

“…., analysis of energy consumption and demand forecasting using deep learning-based time series techniques such as Long short-term memory (LSTM), Bi-directional Long short-term memory (BiLSTM), Gated recurrent unit (GRU), and Bidirectional Gated recurrent units (BiGRU). …”
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WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches by Shehla Gul, Sobia Arshad, Sanay Muhammad Umar Saeed, Adeel Akram, Muhammad Awais Azam

Subjects: “…deep learning (DL)…”
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A Data-Driven Fault Prediction Method for Nuclear Power Systems Based on End-to-End Deep Learning Framework by Lu Chao, Chunbing Wang, Shuai Chen, Qizhi Duan, Hongyun Xie

“…At the same time, due to the rapid development of deep learning technology, it has become a meaningful development direction to predict the fault state of nuclear power plants within the framework of supervised deep learning. …”
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Optimizing hip MRI: enhancing image quality and elevating inter-observer consistency using deep learning-powered reconstruction by Yimeng Kang, Wenjing Li, Qingqing Lv, Qiuying Tao, Jieping Sun, Jinghan Dang, Xiaoyu Niu, Zijun Liu, Shujian Li, Zanxia Zhang, Kaiyu Wang, Baohong Wen, Jingliang Cheng, Yong Zhang, Weijian Wang

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BiST-SA-LSTM: A Deep Learning Framework for End-to-End Prediction of Mesoscale Eddy Distribution in Ocean by Yaoran Chen, Zijian Zhao, Yaojun Yang, Xiaowei Li, Yan Peng, Hao Wu, Xi Zhou, Dan Zhang, Hongyu Wei

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A deep learning model for assistive decision-making during robot-aided rehabilitation therapies based on therapists’ demonstrations by David Martínez-Pascual, José M. Catalán, Luís D. Lledó, Andrea Blanco-Ivorra, Nicolás García-Aracil

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An endoscopic ultrasound-based interpretable deep learning model and nomogram for distinguishing pancreatic neuroendocrine tumors from pancreatic cancer by Nan Yi, Shuangyang Mo, Yan Zhang, Qi Jiang, Yingwei Wang, Cheng Huang, Shanyu Qin, Haixing Jiang

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Deep learning-based synthetic CT for dosimetric monitoring of combined conventional radiotherapy and lattice boost in large lung tumors by Hongwei Zeng, Xiangyu E, Minghe Lv, Su Zeng, Yue Feng, Wenhao Shen, Wenhui Guan, Yang Zhang, Ruping Zhao, Jingping Yu

Subjects: “…Deep learning…”
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Towards Deep Learning in Online Courses: A Case Study in Cross-Pollinating Universal Design for Learning and Dialogic Teaching by Qiongli Zhu, Sarfaroz Niyozov

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Comparative analysis of deep learning and radiomic signatures for overall survival prediction in recurrent high-grade glioma treated with immunotherapy by Qi Wan, Clifford Lindsay, Chenxi Zhang, Jisoo Kim, Xin Chen, Jing Li, Raymond Y. Huang, David A. Reardon, Geoffrey S. Young, Lei Qin

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Leveraging advanced deep learning and machine learning approaches for snow depth prediction using remote sensing and ground data by Haytam Elyoussfi, Abdelghani Boudhar, Salwa Belaqziz, Mostafa Bousbaa, Karima Nifa, Bouchra Bargam, Abdelghani Chehbouni

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Retracted: Extraction and Analysis of Influencing Factors of Scientific and Technological Ability Improvement of University Teachers Based on Deep Learning Model by Advances in Multimedia

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Re-locative guided search optimized self-sparse attention enabled deep learning decoder for quantum error correction by Umesh Uttamrao Shinde, Ravikumar Bandaru

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Predictive modelling of hexagonal boron nitride nanosheets yield through machine and deep learning: An ultrasonic exfoliation parametric evaluation by Jerrin Joy Varughese, Sreekanth M․S․

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Deteksi Kejadian Lalu Lintas pada Teks Twitter dengan Pendekatan Klasidikasi Multi-Label Berbasis Deep Learning by Luthfi Atikah, Diana Purwitasari, Nanik Suciati

“…Klasifikasi dilakukan dengan menggunakan pendekatan deep learning (CNN dan LSTM) dan word embedding (word2vec dan fastText) dengan augmentasi dan non-augmentasi data. …”
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