Yuanyuan Tian

Orcid: 0000-0003-4432-1546

Affiliations:
  • Shanghai Jiao Tong University, School of Mechanical Engineering, Shanghai, China


According to our database1, Yuanyuan Tian authored at least 16 papers between 2023 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2026
Spatial-temporal hierarchical decoupled masked autoencoder: A self-supervised learning framework for electrocardiogram.
Expert Syst. Appl., 2026

Unsupervised artificial intelligence model of arrhythmia diagnosis: Improving model performance on different ECG datasets.
Biomed. Signal Process. Control., 2026

2025
EDDM: A Novel ECG Denoising Method Using Dual-Path Diffusion Model.
IEEE Trans. Instrum. Meas., 2025

An early warning method for arrhythmias in long-term ECGs based on self-supervised learning and LSTM.
Knowl. Based Syst., 2025

BioCross: A cross-modal framework for unified representation of multi-modal biosignals with heterogeneous metadata fusion.
Inf. Fusion, 2025

Multi-task learning for multi-label electrocardiogram disease detection via point-level delineation-guided fusion.
Eng. Appl. Artif. Intell., 2025

2024
Lightweight Optimization of Deep Learning Models for Accurate Arrhythmia Detection in Clinical 12-Lead ECG Data.
IEEE Trans. Instrum. Meas., 2024

Differentiated knowledge distillation: Patient-specific single-sample personalization for electrocardiogram diagnostic models.
Eng. Appl. Artif. Intell., 2024

M-XAF: Medical explainable diagnosis system of atrial fibrillation based on medical knowledge and semantic representation fusion.
Eng. Appl. Artif. Intell., 2024

Automatic multi-label diagnosis of single-lead ECG using novel hybrid residual recurrent convolutional neural networks.
Biomed. Signal Process. Control., 2024

Pruned lightweight neural networks for arrhythmia classification with clinical 12-Lead ECGs.
Appl. Soft Comput., 2024

A self-supervised framework for computer-aided arrhythmia diagnosis.
Appl. Soft Comput., 2024

2023
An Interpretable Residual Neural Network for the Diagnosis of Myocardial Infarction.
Proceedings of the Fuzzy Systems and Data Mining IX, 2023

Evaluate the Correlation Between Electrocardiogram Age and Cardiovascular Disease Using a 12-lead ECG Dataset.
Proceedings of the Fuzzy Systems and Data Mining IX, 2023

A Novel Personalized Incremental Arrhythmias Classification Method for ECG Monitoring.
Proceedings of the Fuzzy Systems and Data Mining IX, 2023

ECG Quality Assessment Framework by Using Attentional Convolution Neural Network.
Proceedings of the Fuzzy Systems and Data Mining IX, 2023


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