Mediv

Jan. 2024

Artificial Intelligence in Medicine (IF 7.5)

Prognostic prediction of sepsis patient using transformer with skip connected token for tabular data

#Biosignal

Jan. 2024

IEEE Transactions on Neural Networks and Learning Systems (IF 14.26)

A Novel Generator with Auxiliary Branch for Improving GAN performance

#GAN

Jun. 2023

Computer methods and programs in biomedicine (IF 7.03)

FT-GAT: Graph neural network for predicting spontaneous breathing trial success in patients with mechanical ventilation

#Biosignal

Apr. 2023

IEEE Journal of Biomedical and Health Informatics (IF 7.02)

Real-Time Prediction for Neonatal Endotracheal Intubation Using Multimodal Transformer Network

#Biosignal

Apr. 2023

Scientific Reports (IF 5)

Predicting the Need for Intubation Within 3 Hours in the Neonatal Intensive Care Unit Using a Multimodal Deep Neural Network

#Biosignal

Jan. 2023

Advanced Intelligent System (IF 7.29)

Multimodal Neural Network for Recurrence Prediction of Papillary Thyroid Carcinoma

#Biosignal

Sep. 2022

Journal of Healthcare Engineering (IF 4.22)

Deep Learning Model for Predicting Rhythm Outcomes after Radiofrequency Catheter Ablation In Patients with Atrial fibrillation

#Biosignal

Sep. 2022

Computers in Biology and Medicine (IF 6.69)

Automated Diagnosis of Atrial Fibrillation Using ECG Component-Aware Transformer

#Biosignal

Sep. 2022

Applied Intelligence (IF 5.02)

PConv: Simple yet Effective Convolutional Layer for Generative Adversarial Network

#GAN

Jan. 2021

Applied Intelligence (IF 5.09)

Generative Residual Block for Image Generation

#GAN

Jan. 2021

IEEE Transactions on Neural Networks and Learning Systems (IF 14.26)

Simple yet Effective Way for Improving the Performance of GAN

#GAN

Nov. 2020

IEEE Access (IF 3.37)

Detail Restoration and Tone Mapping Networks for X-ray Security Inspection

#AI

Prognostic prediction of sepsis patient using transformer with skip connected token for tabular data

A Novel Generator with Auxiliary Branch for Improving GAN performance

FT-GAT: Graph neural network for predicting spontaneous breathing trial success in patients with mechanical ventilation

Real-Time Prediction for Neonatal Endotracheal Intubation Using Multimodal Transformer Network

Predicting the Need for Intubation Within 3 Hours in the Neonatal Intensive Care Unit Using a Multimodal Deep Neural Network

Multimodal Neural Network for Recurrence Prediction of Papillary Thyroid Carcinoma

Deep Learning Model for Predicting Rhythm Outcomes after Radiofrequency Catheter Ablation In Patients with Atrial fibrillation

Automated Diagnosis of Atrial Fibrillation Using ECG Component-Aware Transformer

Image generation with self pixel-wise normalization

Generative Convolution Layer for Image Generation

Effective Shortcut Technique for Generative Adversarial Networks

PConv: Simple yet Effective Convolutional Layer for Generative Adversarial Network

Generative Residual Block for Image Generation

Simple yet Effective Way for Improving the Performance of GAN

Detail Restoration and Tone Mapping Networks for X-ray Security Inspection

Prognostic prediction of sepsis patient using transformer with skip connected token for tabular data

A Novel Generator with Auxiliary Branch for Improving GAN performance

FT-GAT: Graph neural network for predicting spontaneous breathing trial success in patients with mechanical ventilation

Real-Time Prediction for Neonatal Endotracheal Intubation Using Multimodal Transformer Network

Predicting the Need for Intubation Within 3 Hours in the Neonatal Intensive Care Unit Using a Multimodal Deep Neural Network

Multimodal Neural Network for Recurrence Prediction of Papillary Thyroid Carcinoma

Deep Learning Model for Predicting Rhythm Outcomes after Radiofrequency Catheter Ablation In Patients with Atrial fibrillation

Automated Diagnosis of Atrial Fibrillation Using ECG Component-Aware Transformer

Image generation with self pixel-wise normalization

Generative Convolution Layer for Image Generation

Effective Shortcut Technique for Generative Adversarial Networks

PConv: Simple yet Effective Convolutional Layer for Generative Adversarial Network

Generative Residual Block for Image Generation

Simple yet Effective Way for Improving the Performance of GAN

Detail Restoration and Tone Mapping Networks for X-ray Security Inspection