Area of research
Artificial Intelligence · Nephrology
Research interest
Research interests include Thyroid Cancer Diagnosis and Treatment, Anomaly Detection Techniques and Applications, Text and Document Classification Technologies, and Dialysis and Renal Disease Management.
Multimodal fusion of spatial–temporal and frequency representations for enhanced ECG classification
Self-supervised learning for remaining useful life prediction using simple triplet networks
Harnessing heterogeneous graph neural networks for Dynamic Job-Shop Scheduling Problem solutions
ECG-STAR: Spatio-temporal attention residual networks for multi-label ECG abnormality classification
Anomaly detection and segmentation in industrial images using multi-scale reverse distillation
Comparative outcomes of retroperitoneal partial nephrectomy for cT1 and cT2 renal tumors: a single-center experience.
Temporal attention for photovoltaic power forecasting using all-sky imagery
Predicting NSAID-associated cardiac mortality: A deep learning approach to 12-lead ECG analysis
Dynamic Job-Shop Scheduling via Graph Attention Networks and Deep Reinforcement Learning
DualDomain-AttenNet: Synergizing time–frequency analysis and attention mechanisms for Motor Imagery BCI enhancement
Temporal learning in predictive health management using channel-spatial attention-based deep neural networks
A bagging approach for improved predictive accuracy of intradialytic hypotension during hemodialysis treatment.
Dynamic Job-Shop Scheduling Problems Using Graph Neural Network and Deep Reinforcement Learning
Dynamic Parallel Machine Scheduling With Deep Q-Network
A deep learning sequence model based on self-attention and convolution for wind power prediction
Prediction of Blood Glucose Concentration Based on OptiScanner and XGBoost in ICU
The influence of the Pringle maneuver in laparoscopic hepatectomy: continuous monitor of hemodynamic change can predict the perioperatively physiological reservation.
Learning From Imbalanced Data With Deep Density Hybrid Sampling
A Deep Learning-Enabled Electrocardiogram Model for the Identification of a Rare Inherited Arrhythmia: Brugada Syndrome.
Predicting the Wafer Material Removal Rate for Semiconductor Chemical Mechanical Polishing Using a Fusion Network
Kidney Function Trajectory within Six Months after Acute Kidney Injury Inpatient Care and Subsequent Adverse Kidney Outcomes: A Retrospective Cohort Study.
Prediction and Clinically Important Factors of Acute Kidney Injury Non-recovery.
Actor-Critic Deep Reinforcement Learning for Solving Job Shop Scheduling Problems
Model-Based Synthetic Sampling for Imbalanced Data
Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study.
Predicting Short-term Survival after Liver Transplantation using Machine Learning.
Metric-Based Semi-Supervised Regression
Time Series Classification With Multivariate Convolutional Neural Network
Epileptic Seizure Prediction With Multi-View Convolutional Neural Networks
Multivariate Time Series Early Classification with Interpretability Using Deep Learning and Attention Mechanism