| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Ruiwen Zhou, J Philip Miller, Mae Gordon, Michael Kass, Mingquan Lin, Yifan Peng, Fuhai Li, Jiarui Feng, Lei Li. Deep learning models to predict primary open-angle glaucoma. Stat (International Statistical Institute). vol 13. issue 1. 2024-09-02. PMID:39220673. |
when evaluated on the ocular hypertension treatment study (ohts) dataset, our proposed convolutional neural network (cnn)-long short-term memory (lstm) emerged as the top-performing model among all those examined. |
2024-09-02 |
2024-09-04 |
human |
| Shilie He, Meiling Yu, Yiqiang Chen, Zhenwei Zhou, Lubin Yu, Chao Zhang, Yuanhua N. Prediction of IGBT Gate Oxide Layer's Performance Degradation Based on MultiScaleFormer Network. Micromachines. vol 15. issue 8. 2024-09-01. PMID:39203636. |
multiscaleformer showed the highest fitting accuracy compared with the long short-term memory (lstm), convolutional neural network (cnn), support vector regression (svr), gaussian process regression (gpr), cnn-lstm, and transformer models in our experiment. |
2024-09-01 |
2024-09-04 |
Not clear |
| Guo-Shing Huang, Meng-Hua Yen, Chia-Chun Chang, Chung-Liang Lai, Chi-Chun Che. Development of an individualized stable and force-reducing lower-limb exoskeleton. Biomedical physics & engineering express. vol 10. issue 5. 2024-08-30. PMID:39212326. |
users' joint angles and the center of pressure (cop) of one of their soles were input into a convolutional neural network (cnn)-long short-term memory (lstm) model to evaluate and adjust the exoskeleton control scheme. |
2024-08-30 |
2024-09-04 |
Not clear |
| Xinrong Xie, Zhaocai Wang, Manli Xu, Nannan X. Daily PM2.5 concentration prediction based on variational modal decomposition and deep learning for multi-site temporal and spatial fusion of meteorological factors. Environmental monitoring and assessment. vol 196. issue 9. 2024-08-29. PMID:39207594. |
this study introduces a new hybrid model within the "decomposition-prediction-integration" (dpi) framework, which combines variational modal decomposition (vmd), causal convolutional neural network (cnn), bidirectional long short-term memory (bilstm), and attention mechanism (am), named as vcba, for spatio-temporal fusion of multi-site data to forecast daily pm2.5 concentrations in a city. |
2024-08-29 |
2024-09-04 |
Not clear |
| Chengguan Wang, Guangping Wang, Tao Wang, Xiyao Xiong, Zhongchuan Ouyang, Tao Gon. Exploring the Processing Paradigm of Input Data for End-to-End Deep Learning in Tool Condition Monitoring. Sensors (Basel, Switzerland). vol 24. issue 16. 2024-08-29. PMID:39204994. |
then an improved hybrid model that combines a convolutional neural network (cnn) and bidirectional long short-term memory (bilstm) was employed to validate the model's performance. |
2024-08-29 |
2024-09-04 |
Not clear |
| Muhammad Saqib Rashid, Yanhong Wang, Yilong Yin, Balal Yousaf, Shaojun Jiang, Adeel Feroz Mirza, Bing Chen, Xiang Li, Zhongzhen Li. Quantitative Soil Characterization for Biochar-Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization. Toxics. vol 12. issue 8. 2024-08-28. PMID:39195637. |
in this study, long short-term memory (lstm), bidirectional gated recurrent unit (bigru), and 5-layer cnn convolutional neural networks (cnns) were applied for risk assessments to establish a framework for evaluating cd risk in bc amended soils to predict cd transformation. |
2024-08-28 |
2024-08-30 |
Not clear |
| Himanshu Singh, Joana M Warnecke, Alexander Picker, Nagarajan Ganapathy, Thomas M Desern. Multimodal Signal Fusion for Heartbeat Monitoring on eScooters. Studies in health technology and informatics. vol 316. 2024-08-23. PMID:39176954. |
we explore heartbeat monitoring using electrocardiography (ecg) and photoplethysmography (ppg) and evaluate four signal fusion approaches based on convolutional neural network (cnn) and long short-term memory (lstm) architectures. |
2024-08-23 |
2024-08-25 |
Not clear |
| Cyrille Yetuyetu Kesiku, Begonya Garcia-Zapirai. AI-Enhanced Lung Cancer Prediction: A Hybrid Model's Precision Triumph. IEEE journal of biomedical and health informatics. vol PP. 2024-08-22. PMID:39172617. |
this study introduces a hybrid deep learning model, incorporating convolutional neural networks (cnn) and bidirectional long short-term memory networks (bilstm), designed for lung cancer detection from patients' medical notes. |
2024-08-22 |
2024-08-25 |
Not clear |
| Muhammad Kamran Khan, Mohamad Abou Houran, Kimmo Kauhaniemi, Muhammad Hamza Zafar, Majad Mansoor, Saad Rashi. Efficient state of charge estimation of lithium-ion batteries in electric vehicles using evolutionary intelligence-assisted GLA-CNN-Bi-LSTM deep learning model. Heliyon. vol 10. issue 15. 2024-08-22. PMID:39170306. |
our model uniquely integrates a convolutional neural network (cnn) with bidirectional long short-term memory (bi-lstm), optimized through evolutionary intelligence, enabling an advanced level of precision in soc estimation. |
2024-08-22 |
2024-08-24 |
Not clear |
| Huanhuan Li, Wei Sheng, Selorm Yao-Say Solomon Adade, Xorlali Nunekpeku, Quansheng Che. Investigation of heat-induced pork batter quality detection and change mechanisms using Raman spectroscopy coupled with deep learning algorithms. Food chemistry. vol 461. 2024-08-22. PMID:39173265. |
subsequently, convolutional neural networks (cnn), long short-term memory neural networks (lstm), and cnn-lstm were comparatively used to predict gel strength and whiteness in batters based on the raman spectrum. |
2024-08-22 |
2024-08-25 |
Not clear |
| Mohammed Jawad Ahmed Alathari, Yousif Al Mashhadany, Ahmed Ashrif A Bakar, Mohd Hadri Hafiz Mokhtar, Mohd Saiful Dzulkefly Bin Zan, Norhana Arsa. COVID-19 IgG Antibodies Detection Based on CNN-BiLSTM Algorithm Combined with Fiber-Optic Dataset. Journal of virological methods. 2024-08-18. PMID:39154936. |
in this study, we present pioneering research on covid-19 detection using a hybrid model that combines convolutional neural networks (cnn) with a bi-directional long short-term memory (bi-lstm) network, in conjunction with fiber optic data for sars-cov-2 immunoglobulin g (igg) antibodies. |
2024-08-18 |
2024-08-21 |
Not clear |
| Nek Dil Khan, Javed Ali Khan, Jianqiang Li, Tahir Ullah, Qing Zha. Mining software insights: uncovering the frequently occurring issues in low-rating software applications. PeerJ. Computer science. vol 10. 2024-08-15. PMID:39145243. |
also, an experimental study comparing various ml and dl algorithms, including multinomial naive bayes (mnb), logistic regression (lr), random forest (rf), multi-layer perception (mlp), k-nearest neighbors (knn), adaboost, voting, convolutional neural network (cnn), long short-term memory (lstm), bidirectional long short term memory (bilstm), gated recurrent unit (gru), bidirectional gated recurrent unit (bigru), and recurrent neural network (rnn) classifiers, achieved satisfactory results in classifying end-user feedback to commonly occurring issues. |
2024-08-15 |
2024-08-17 |
Not clear |
| John D Mayfield, Dana Ataya, Mahmoud Abdalah, Olya Stringfield, Marilyn M Bui, Natarajan Raghunand, Bethany Niell, Issam El Naq. Presurgical Upgrade Prediction of DCIS to Invasive Ductal Carcinoma Using Time-dependent Deep Learning Models with DCE MRI. Radiology. Artificial intelligence. vol 6. issue 5. 2024-08-14. PMID:38900042. |
binary classification was implemented with convolutional neural network (cnn)-long short-term memory (lstm) architectures benchmarked against traditional cnns without manual segmentation of the lesions. |
2024-08-14 |
2024-08-16 |
Not clear |
| Jianhao Nie, Huazhong Shu, Fuzhi W. An epilepsy classification based on FFT and fully convolutional neural network nested LSTM. Frontiers in neuroscience. vol 18. 2024-08-14. PMID:39139499. |
in this study, a classification method is proposed that use fast fourier transform (fft) extraction in conjunction with convolutional neural networks (cnn) and long short-term memory (lstm) models. |
2024-08-14 |
2024-08-16 |
Not clear |
| Xiaoqi Fan, Xiaoxin Mao, Longsheng Wang, Songnian Fu, Anbang Wang, Yuncai Wan. Improving decryption quality of optical chaos communication using neural networks. Optics letters. vol 49. issue 15. 2024-08-02. PMID:39090955. |
here, we demonstrate that the use of a convolutional neural network (cnn) with a bidirectional long short-term memory (lstm) layer can reduce the decryption ber in an optical chaos communication system based on common-signal-induced semiconductor laser synchronization. |
2024-08-02 |
2024-08-05 |
Not clear |
| Zhilong Guo, Xiangnan Jing, Yuewei Ling, Ying Yang, Nan Jing, Rui Yuan, Yixin Li. Optimized air quality management based on air quality index prediction and air pollutants identification in representative cities in China. Scientific reports. vol 14. issue 1. 2024-08-02. PMID:39095454. |
we proposed a new model for daily aqi prediction, termed vmd-csa-cnn-lstm, which employed advanced machine learning techniques, including convolutional neural networks (cnn) and long short-term memory (lstm) networks, and leveraged the chameleon swarm algorithm (csa) for hyperparameter optimization, integrated through a variational mode decomposition approach. |
2024-08-02 |
2024-08-06 |
Not clear |
| MohammadReza Safari, Reza Shalbaf, Sara Bagherzadeh, Ahmad Shalba. Classification of mental workload with EEG analysis by using effective connectivity and a hybrid model of CNN and LSTM. Computer methods in biomechanics and biomedical engineering. 2024-08-01. PMID:39086252. |
then, we propose a deep hybrid model based on pre-trained convolutional neural networks (cnn) and long short-term memory (lstm) for the classification of workload levels. |
2024-08-01 |
2024-08-03 |
human |
| Qingchun Guo, Zhenfang He, Zhaosheng Wan. Monthly climate prediction using deep convolutional neural network and long short-term memory. Scientific reports. vol 14. issue 1. 2024-07-31. PMID:39085577. |
the different artificial intelligence models are proposed to simulate climate parameters of jinan city in china, include artificial neural network (ann), recurrent nn (rnn), long short-term memory neural network (lstm), deep convolutional nn (cnn), and cnn-lstm. |
2024-07-31 |
2024-08-03 |
human |
| Khadija Begum, Md Ariful Islam Mozumder, Moon-Il Joo, Hee-Cheol Ki. BFLIDS: Blockchain-Driven Federated Learning for Intrusion Detection in IoMT Networks. Sensors (Basel, Switzerland). vol 24. issue 14. 2024-07-27. PMID:39065989. |
for classification, we implemented an adaptive max pooling-based convolutional neural network (cnn) and a modified bidirectional long short-term memory (bilstm) with attention and residual connections on edge-iiotset and ton-iot datasets. |
2024-07-27 |
2024-07-29 |
Not clear |
| Yilin Mao, He Li, Yang Xu, Shuangshuang Wang, Xinyue Yin, Kai Fan, Zhaotang Ding, Yu Wan. Early detection of gray blight in tea leaves and rapid screening of resistance varieties by hyperspectral imaging technology. Journal of the science of food and agriculture. 2024-07-20. PMID:39030928. |
combining convolution neural network (cnn), long short-term memory (lstm), and support vector machine (svm) algorithms, the early detection model of gb disease, and the rapid screening model of resistant varieties were established. |
2024-07-20 |
2024-07-24 |
Not clear |