| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Doaa A Abdel Hady, Tarek Abd El-Hafee. Revolutionizing core muscle analysis in female sexual dysfunction based on machine learning. Scientific reports. vol 14. issue 1. 2024-02-27. PMID:38413786. |
we evaluated the performance of multiple models, including multi-layer perceptron (mlp), long short-term memory (lstm), convolutional neural network (cnn), recurrent neural network (rnn), elasticnetcv, random forest regressor, svr, and bagging regressor. |
2024-02-27 |
2024-03-01 |
Not clear |
| Umesh Kumar Lilhore, Surjeet Dalal, Neeraj Varshney, Yogesh Kumar Sharma, K B V Brahma Rao, V V R Maheswara Rao, Roobaea Alroobaea, Sarita Simaiya, Martin Margala, Prasun Chakrabart. Prevalence and risk factors analysis of postpartum depression at early stage using hybrid deep learning model. Scientific reports. vol 14. issue 1. 2024-02-24. PMID:38402249. |
this research proposes a hybrid ppdd framework that combines improved bi-directional long short-term memory (ibi-lstm) with transfer learning (tl) based on two convolutional neural network (cnn) architectures, respectively cnn-text and cnn audio. |
2024-02-24 |
2024-02-27 |
Not clear |
| Junde Chen, Yuxin Wen, Michael Pokojovy, Tzu-Liang Bill Tseng, Peter McCaffrey, Alexander Vo, Eric Walser, Scott Moe. Multi-modal learning for inpatient length of stay prediction. Computers in biology and medicine. vol 171. 2024-02-21. PMID:38382388. |
specifically, a convolutional neural network (cnn) model, which we termed crxmdl, is designed for chest x-ray (cxr) image data, two long short-term memory networks are used to extract features from long text data, and a novel attention-embedded 1d convolutional neural network is developed to extract useful information from numerical data. |
2024-02-21 |
2024-02-24 |
Not clear |
| Serkan Kartal, Muzaffer Can Iban, Aliihsan Sekerteki. Next-level vegetation health index forecasting: A ConvLSTM study using MODIS Time Series. Environmental science and pollution research international. 2024-02-14. PMID:38353824. |
to achieve this objective, the study proposes employing a combined convolutional neural network (cnn) and a specific type of recurrent neural network (rnn) called long short-term memory (lstm), known as convlstm. |
2024-02-14 |
2024-02-16 |
Not clear |
| R Janani Abinaya, G Rajakuma. Accurate Liver Fibrosis Detection Through Hybrid MRMR-BiLSTM-CNN Architecture with Histogram Equalization and Optimization. Journal of imaging informatics in medicine. 2024-02-13. PMID:38351226. |
this research presents a novel computer-aided diagnosis model for liver fibrosis using a hybrid approach of minimum redundancy maximum relevance (mrmr) feature selection, bidirectional long short-term memory (bilstm), and convolutional neural networks (cnn). |
2024-02-13 |
2024-02-16 |
Not clear |
| Bin Wu, Xinyu Wu, Peng Li, Youbing Gao, Jiangbo Si, Naofal Al-Dhahi. Efficient FPGA Implementation of Convolutional Neural Networks and Long Short-Term Memory for Radar Emitter Signal Recognition. Sensors (Basel, Switzerland). vol 24. issue 3. 2024-02-10. PMID:38339606. |
to tackle this problem, this paper proposes a resource reuse computing acceleration platform based on field programmable gate arrays (fpga), and implements a one-dimensional (1d) convolutional neural network (cnn) and long short-term memory (lstm) neural network (nn) model for radar emitter signal recognition, directly targeting the intermediate frequency (if) data of radar emitter signal for classification and recognition. |
2024-02-10 |
2024-02-12 |
Not clear |
| Xiangnan Dang, Wentao Li, Jasmine Zou, Brian Cong, Yuanfang Gua. Assessing the impact of body location on the accuracy of detecting daily activities with accelerometer data. iScience. vol 27. issue 2. 2024-02-06. PMID:38318391. |
here, we conducted a trial focusing on the impact of sensor placement in predicting 21 common activities using convolutional neural networks (cnn) and long short-term memory networks (lstm). |
2024-02-06 |
2024-02-09 |
Not clear |
| Musa Aslan, Muhammet Baykara, Talha Burak Alaku. LieWaves: dataset for lie detection based on EEG signals and wavelets. Medical & biological engineering & computing. 2024-02-04. PMID:38311647. |
in the last stage, each obtained feature vector was classified separately using convolutional neural network (cnn), long short-term memory (lstm), and cnnlstm hybrid algorithms. |
2024-02-04 |
2024-02-07 |
human |
| Liguo Zhang, Liangyu Zhao, Yongtao Ya. A hybrid neural network-based intelligent body posture estimation system in sports scenes. Mathematical biosciences and engineering : MBE. vol 21. issue 1. 2024-02-02. PMID:38303452. |
specifically, a cnn unit and a long short-term memory (lstm) unit are employed as the backbone network in order to extract key-point information and temporal information from video frames, respectively. |
2024-02-02 |
2024-02-04 |
Not clear |
| Chang June Lee, Jung Keun Le. IMU-Based Energy Expenditure Estimation for Various Walking Conditions Using a Hybrid CNN-LSTM Model. Sensors (Basel, Switzerland). vol 24. issue 2. 2024-01-23. PMID:38257507. |
in this study, we present a hybrid model comprising a convolutional neural network (cnn) and long short-term memory (lstm) to estimate the steady-state energy expenditure under various walking conditions based solely on imu data. |
2024-01-23 |
2024-01-25 |
Not clear |
| Tabish Saeed, Aneeqa Ijaz, Ismail Sadiq, Haneya Naeem Qureshi, Ali Rizwan, Ali Imra. An AI-Enabled Bias-Free Respiratory Disease Diagnosis Model Using Cough Audio. Bioengineering (Basel, Switzerland). vol 11. issue 1. 2024-01-22. PMID:38247932. |
a hybrid of a convolutional neural networks (cnn) and long short-term memory (lstm) networks is proposed for the feature encoder module of rbf-net. |
2024-01-22 |
2024-01-24 |
Not clear |
| Zhaohua Wang, Longzhen Duan, Dongsheng Shuai, Taorong Qi. Research on water environmental indicators prediction method based on EEMD decomposition with CNN-BiLSTM. Scientific reports. vol 14. issue 1. 2024-01-19. PMID:38243034. |
to address this issue, this paper introduces a hybrid water quality index prediction model based on ensemble empirical mode decomposition (eemd), combined with convolutional neural network (cnn) and bidirectional long short-term memory network (bilstm). |
2024-01-19 |
2024-01-22 |
Not clear |
| Honglei Wang, Tao Huang, Dong Wang, Wenliang Zeng, Yanjing Sun, Lin Zhan. MSCAN: multi-scale self- and cross-attention network for RNA methylation site prediction. BMC bioinformatics. vol 25. issue 1. 2024-01-17. PMID:38233745. |
bidirectional long short-term memory (bilstm), convolutional neural network (cnn), and the transformer have demonstrated achievements in modification site prediction. |
2024-01-17 |
2024-01-20 |
Not clear |
| Junbo Niu, Bin Miao, Jiaxu Guo, Zhifeng Ding, Yin He, Zhiyu Chi, Feilong Wang, Xinxin M. Leveraging Deep Neural Networks for Estimating Vickers Hardness from Nanoindentation Hardness. Materials (Basel, Switzerland). vol 17. issue 1. 2024-01-11. PMID:38204003. |
by conducting rigorous experimentation and obtaining corresponding nanoindentation data, we evaluated the performance of four distinct neural network architectures: multilayer perceptron (mlp), convolutional neural network (cnn), long short-term memory network (lstm), and transformer. |
2024-01-11 |
2024-01-13 |
Not clear |
| Dmitrii Kaplun, Surajit Deka, Arunabh Bora, Nupur Choudhury, Jyotishman Basistha, Bhaswadeep Purkayastha, Ifthikaruz Zaman Mazumder, Vyacheslav Gulvanskii, Kandarpa Kumar Sarma, Debashis Dev Misr. An intelligent agriculture management system for rainfall prediction and fruit health monitoring. Scientific reports. vol 14. issue 1. 2024-01-04. PMID:38177254. |
the proposed system based on an ai aided model makes use of a convolutional neural network (cnn) with long short-term memory (lstm) layer for rainfall prediction and a cnn with softmax layer along with a few deep learning pre-trained models for fruit health monitoring. |
2024-01-04 |
2024-01-07 |
Not clear |
| Chen Huang, Ye Zhou, Tao Wu, Mingyue Zhang, Yu Qi. A cellular automata model coupled with partitioning CNN-LSTM and PLUS models for urban land change simulation. Journal of environmental management. vol 351. 2023-12-22. PMID:38134506. |
to address these gaps, this study proposes a novel model called kclp-ca, which integrates k-means, a convolutional neural network (cnn), a long and short-term memory neural network (lstm), and the popular patch-generation land use model (plus). |
2023-12-22 |
2023-12-25 |
Not clear |
| Xing Wei, Shitao Cheng, Rui Chen, Zijian Wang, Yanjun L. ANN deformation prediction model for deep foundation pit with considering the influence of rainfall. Scientific reports. vol 13. issue 1. 2023-12-19. PMID:38114655. |
in the study, an ann model is proposed based on the wave transform (wt), copula method, convolutional neural network (cnn) and long short-term memory neural network (lstm). |
2023-12-19 |
2023-12-23 |
Not clear |
| Xizheng Ke, Qingyang Zhang, Huanhuan Qi. CNN neural network temporal feature storage structure fusion for the visible channel equalization algorithm. Applied optics. vol 62. issue 35. 2023-12-18. PMID:38108694. |
this paper proposes an equalization algorithm based on the structure of a convolutional neural network (cnn), combining time series feature length and long short-term memory (lstm), and adding a residual structure. |
2023-12-18 |
2023-12-21 |
Not clear |
| Zilu Wang, Ian Daly, Junhua L. An Evaluation of Hybrid Deep Learning Models for Classifying Multiple Lower Limb Actions. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2023. 2023-12-12. PMID:38082609. |
recent research has demonstrated that deep learning models, such as convolutional neural network (cnn) and long short-term memory (lstm), are successful in a wide range of classification applications. |
2023-12-12 |
2023-12-17 |
Not clear |
| Anant Jain, Lalan Kuma. EEG Cortical Source Feature based Hand Kinematics Decoding using Residual CNN-LSTM Neural Network. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2023. 2023-12-12. PMID:38082886. |
a residual convolutional neural network (cnn) - long short-term memory (lstm) based kinematics decoding model is proposed that utilizes motor neural information present in pre-movement brain activity. |
2023-12-12 |
2023-12-17 |
Not clear |