| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Wentao Gao, Dali Xu, Hongfei Li, Junping Du, Guohua Wang, Dan L. Identification of adaptor proteins by incorporating deep learning and PSSM profiles. Methods (San Diego, Calif.). 2022-11-25. PMID:36427763. |
however, ordinary neural network models cannot correlate the contextual information in pssm profiles well, so these studies usually process 20×n (n>20) pssm into 20×20 dimensions, which results in the loss of a large amount of protein information; this research proposes an efficient method that combines one-dimensional convolution (1-d cnn) and a bidirectional long short-term memory network (bilstm) to identify adaptor proteins. |
2022-11-25 |
2023-08-14 |
Not clear |
| Akella S Narasimha Raju, Kayalvizhi Jayavel, T Rajalakshm. ColoRectalCADx: Expeditious Recognition of Colorectal Cancer with Integrated Convolutional Neural Networks and Visual Explanations Using Mixed Dataset Evidence. Computational and mathematical methods in medicine. vol 2022. 2022-11-21. PMID:36404909. |
the cadx system comprises five stages: convolutional neural networks (cnn), support vector machine (svm), long short-term memory (lstm), visual explanation such as gradient-weighted class activation mapping (grad-cam), and semantic segmentation phases. |
2022-11-21 |
2023-08-14 |
human |
| Lei Cao, Hailiang Wu, Shugeng Chen, Yilin Dong, Changming Zhu, Jie Jia, Chunjiang Fa. A Novel Deep Learning Method Based on an Overlapping Time Window Strategy for Brain-Computer Interface-Based Stroke Rehabilitation. Brain sciences. vol 12. issue 11. 2022-11-11. PMID:36358428. |
for this aim, three different models, a convolutional neural network (cnn), graph isomorphism network (gin), and long short-term memory (lstm), are used for performing the classification task of motor attempt (ma). |
2022-11-11 |
2023-08-14 |
Not clear |
| Johannes Link, Leo Schwinn, Falk Pulsmeyer, Thomas Kautz, Bjoern M Eskofie. xLength: Predicting Expected Ski Jump Length Shortly after Take-Off Using Deep Learning. Sensors (Basel, Switzerland). vol 22. issue 21. 2022-11-11. PMID:36366174. |
we evaluate the performance of a fully connected neural network, a convolutional neural network (cnn), a long short-term memory (lstm), and a resnet architecture to estimate the xlength. |
2022-11-11 |
2023-08-14 |
Not clear |
| Pengyu Fu, Liang Chu, Zhuoran Hou, Zhiqi Guo, Yang Lin, Jincheng H. State-of-Health Prediction Using Transfer Learning and a Multi-Feature Fusion Model. Sensors (Basel, Switzerland). vol 22. issue 21. 2022-11-11. PMID:36366228. |
the model is based on a convolutional neural network (cnn) and a long short-term memory network (lstm). |
2022-11-11 |
2023-08-14 |
Not clear |
| Agus Nursikuwagus, Rinaldi Munir, Masayu Leylia Khodr. Hybrid of Deep Learning and Word Embedding in Generating Captions: Image-Captioning Solution for Geological Rock Images. Journal of imaging. vol 8. issue 11. 2022-11-10. PMID:36354867. |
the proposed model was constructed by a convolutional neural network (cnn), long short-term memory (lstm), and word2vec and gave a dense output of 256 units. |
2022-11-10 |
2023-08-14 |
Not clear |
| Bhaskar Tripathi, Rakesh Kumar Sharm. Modeling Bitcoin Prices using Signal Processing Methods, Bayesian Optimization, and Deep Neural Networks. Computational economics. 2022-11-07. PMID:36337302. |
we found that the deep artificial neural network model created using technical indicators as input data outperformed other benchmark models like long short term memory, bi-directional lstm (bilstm), and convolutional neural network (cnn)-bilstm. |
2022-11-07 |
2023-08-14 |
Not clear |
| Xiangdong Peng, Xiao Zhou, Huaqiang Zhu, Zejun Ke, Congcheng Pa. MSFF-Net: Multi-Stream Feature Fusion Network for surface electromyography gesture recognition. PloS one. vol 17. issue 11. 2022-11-07. PMID:36342906. |
at present, the main applications of deep learning for semg gesture feature extraction are based on convolutional neural network (cnn) structures to capture spatial morphological information of the multichannel semg or based on long short-term memory network (lstm) to extract time-dependent information of the single-channel semg. |
2022-11-07 |
2023-08-14 |
human |
| Vipin Jain, Kanchan Lata Kashya. Ensemble hybrid model for Hindi COVID-19 text classification with metaheuristic optimization algorithm. Multimedia tools and applications. 2022-10-31. PMID:36313485. |
finally, a hybrid of convolution neural network(cnn) and a long short-term memory (lstm) model pair is employed to categorize the sentiments as positive, negative, and neutral. |
2022-10-31 |
2023-08-14 |
Not clear |
| Bomin Wei, Yue Zhang, Xiang Gon. DeepLPI: a novel deep learning-based model for protein-ligand interaction prediction for drug repurposing. Scientific reports. vol 12. issue 1. 2022-10-28. PMID:36307509. |
here, we propose the deeplpi, a novel deep learning-based model that mainly consists of resnet-based 1-dimensional convolutional neural network (1d cnn) and bi-directional long short term memory network (bilstm), to establish an end-to-end framework for protein-ligand interaction prediction. |
2022-10-28 |
2023-08-14 |
Not clear |
| Tsige Tadesse Alemayoh, Masaaki Shintani, Jae Hoon Lee, Shingo Okamot. Deep-Learning-Based Character Recognition from Handwriting Motion Data Captured Using IMU and Force Sensors. Sensors (Basel, Switzerland). vol 22. issue 20. 2022-10-27. PMID:36298192. |
these included vision transformer (vit), dnn (deep neural network), cnn (convolutional neural network), and lstm (long short-term memory). |
2022-10-27 |
2023-08-14 |
human |
| João M Lopes, Joana Figueiredo, Pedro Fonseca, João J Cerqueira, João P Vilas-Boas, Cristina P Santo. Deep Learning-Based Energy Expenditure Estimation in Assisted and Non-Assisted Gait Using Inertial, EMG, and Heart Rate Wearable Sensors. Sensors (Basel, Switzerland). vol 22. issue 20. 2022-10-27. PMID:36298264. |
this work explores and benchmarks the long short-term memory (lstm) and convolutional neural network (cnn) as deep learning regressors. |
2022-10-27 |
2023-08-14 |
human |
| Ahtesham Bakht, Shambhavi Sharma, Duckshin Park, Hyunsoo Le. Deep Learning-Based Indoor Air Quality Forecasting Framework for Indoor Subway Station Platforms. Toxics. vol 10. issue 10. 2022-10-26. PMID:36287838. |
this hybrid framework is an integration of several deep learning frameworks, namely, convolution neural network (cnn), long short-term memory (lstm), and deep neural network (dnn), and is called hybrid cnn-lstm-dnn; it has the characteristics to capture temporal patterns and informative characteristics from the indoor and outdoor air quality parameters compared with the standalone deep learning models. |
2022-10-26 |
2023-08-14 |
Not clear |
| Yan Xu, Lingwei Men. Deconstruction of Risk Prediction of Ischemic Cardiovascular and Cerebrovascular Diseases Based on Deep Learning. Contrast media & molecular imaging. vol 2022. 2022-10-20. PMID:36263000. |
construct the dnn, cnn, and long short-term memory (lstm) network for comparative analysis with dbn-lstm. |
2022-10-20 |
2023-08-14 |
Not clear |
| Basant Agarwal, Mukesh Kumar Gupta, Harish Sharma, Ramesh Chandra Pooni. Siamese-Based Architecture for Cross-Lingual Plagiarism Detection in English-Hindi Language Pairs. Big data. 2022-10-19. PMID:36260373. |
the proposed model combines the convolutional neural network (cnn) and bidirectional long short-term memory (bi-lstm) network to learn the semantic similarity among the cross-lingual sentences for the english-hindi language pairs. |
2022-10-19 |
2023-08-14 |
Not clear |
| Tae Hyong Kim, Jong Hoon Kim, Ji Young Kim, Seung Eel O. Egg Freshness Prediction Model Using Real-Time Cold Chain Storage Condition Based on Transfer Learning. Foods (Basel, Switzerland). vol 11. issue 19. 2022-10-14. PMID:36230158. |
the convolutional neural network (cnn) and long short-term memory (lstm) algorithm are stacked to make one deep learning model with hyperparameter optimization to increase hu value prediction performance. |
2022-10-14 |
2023-08-14 |
Not clear |
| Bingguo Liu, Zhuo Gao, Binghui Lu, Hangcheng Dong, Zeru A. Deep Learning-Based Remaining Useful Life Estimation of Bearings with Time-Frequency Information. Sensors (Basel, Switzerland). vol 22. issue 19. 2022-10-14. PMID:36236501. |
considering the time correlation of signal sequences, a long and short-term memory network is designed in cnn, incorporating the convolutional block attention module, and understanding the decision-making process of the network from the interpretability level. |
2022-10-14 |
2023-08-14 |
Not clear |
| R J Kavitha, C Thiagarajan, P Indira Priya, A Vivek Anand, Essam A Al-Ammar, Madhappan Santhamoorthy, P Chandramoha. Improved Harris Hawks Optimization with Hybrid Deep Learning Based Heating and Cooling Load Prediction on residential buildings. Chemosphere. vol 309. issue Pt 1. 2022-10-10. PMID:36210577. |
in addition, the hdl model involves convolutional neural network (cnn) along with long short-term memory (lstm) and bidirectional long short-term memory (bilstm) for hl and cl prediction process. |
2022-10-10 |
2023-08-14 |
Not clear |
| Yifang Yan. Application of LSTM Neural Network Technology Embedded in English Intelligent Translation. Computational intelligence and neuroscience. vol 2022. 2022-10-07. PMID:36203717. |
the self-attention mechanism is combined with convolutional neural network (cnn) and long-term and short-term memory network (lstm). |
2022-10-07 |
2023-08-14 |
Not clear |
| Honghua Chen, Jian Cen, Zhuohong Yang, Weiwei Si, Hongchao Chen. Fault Diagnosis of the Dynamic Chemical Process Based on the Optimized CNN-LSTM Network. ACS omega. vol 7. issue 38. 2022-10-03. PMID:36188261. |
to address the problem that existing methods have difficulty extracting the dynamic fault features of a chemical process, a fusion model (cs-imlstm) based on a convolutional neural network (cnn), squeeze-and-excitation (se) attention mechanism, and improved long short-term memory network (imlstm) is developed for chemical process fault diagnosis in this paper. |
2022-10-03 |
2023-08-14 |
Not clear |