Ruibin Feng

Ruibin Feng

Arizona State University

H-index: 12

North America-United States

About Ruibin Feng

Ruibin Feng, With an exceptional h-index of 12 and a recent h-index of 11 (since 2020), a distinguished researcher at Arizona State University, specializes in the field of Machine Learning, Medical Imaging, Heart Rhythm Disorders.

His recent articles reflect a diverse array of research interests and contributions to the field:

AUTOMATED, ACCURATE IDENTIFICATION OF VENTRICULAR TACHYCARDIA FROM ELECTRONIC HEALTH RECORDS USING NATURAL LANGUAGE PROCESSING

Systems, methods, and apparatuses for training a deep model to learn contrastive representations embedded within part-whole semantics via a self-supervised learning framework

Image Classification on Hypersphere Loss

Predicting success of atrial fibrillation ablation: comparing machine learning approaches of intracardiac electrograms

Defining the Predictive Ceiling of Electrogram Features Alone for Predicting Outcomes From Atrial Fibrillation Ablation

PO-03-097 DEFINING ELECTRODE CONFIGURATION FOR MAPPING MICROANATOMIC REENTRIES SUSTAINING ATRIAL FIBRILLATION

PO-03-096 DEFINING RECORDING ANTENNA FOR ATRIAL ELECTRODES BY ENDOCARDIAL AND EPICARDIAL COMPUTER MAPPING

Quantifying a spectrum of clinical response in atrial tachyarrhythmias using spatiotemporal synchronization of electrograms

Ruibin Feng Information

University

Position

___

Citations(all)

806

Citations(since 2020)

744

Cited By

262

hIndex(all)

12

hIndex(since 2020)

11

i10Index(all)

16

i10Index(since 2020)

11

Email

University Profile Page

Google Scholar

Ruibin Feng Skills & Research Interests

Machine Learning

Medical Imaging

Heart Rhythm Disorders

Top articles of Ruibin Feng

AUTOMATED, ACCURATE IDENTIFICATION OF VENTRICULAR TACHYCARDIA FROM ELECTRONIC HEALTH RECORDS USING NATURAL LANGUAGE PROCESSING

Journal of the American College of Cardiology

2024/4/2

Systems, methods, and apparatuses for training a deep model to learn contrastive representations embedded within part-whole semantics via a self-supervised learning framework

2024/2/27

Image Classification on Hypersphere Loss

IEEE Transactions on Industrial Informatics

2024/1/12

Predicting success of atrial fibrillation ablation: comparing machine learning approaches of intracardiac electrograms

European Heart Journal

2023/11

Defining the Predictive Ceiling of Electrogram Features Alone for Predicting Outcomes From Atrial Fibrillation Ablation

2023/10/1

PO-03-097 DEFINING ELECTRODE CONFIGURATION FOR MAPPING MICROANATOMIC REENTRIES SUSTAINING ATRIAL FIBRILLATION

Heart Rhythm

2023/5/1

Miguel Rodrigo
Miguel Rodrigo

H-Index: 12

Ruibin Feng
Ruibin Feng

H-Index: 8

PO-03-096 DEFINING RECORDING ANTENNA FOR ATRIAL ELECTRODES BY ENDOCARDIAL AND EPICARDIAL COMPUTER MAPPING

Heart Rhythm

2023/5/1

Miguel Rodrigo
Miguel Rodrigo

H-Index: 12

Ruibin Feng
Ruibin Feng

H-Index: 8

Quantifying a spectrum of clinical response in atrial tachyarrhythmias using spatiotemporal synchronization of electrograms

Europace

2023/5

Systems, methods, and apparatuses for implementing systematic benchmarking analysis to improve transfer learning for medical image analysis

2023/9/28

OBSTRUCTIVE SLEEP APNEA PORTENDS STROKE IN YOUNG INDIVIDUALS WITHOUT ATRIAL FIBRILLATION: A LARGE REGISTRY STUDY

Journal of the American College of Cardiology

2023/3/7

VENTRICULAR TACHYCARDIA PREDICTS ATRIAL FIBRILLATION RECURRENCE POST ABLATION: A PROPENSITY SCORE-MATCHED ANALYSIS OF A LARGE PROSPECTIVE STUDY

Journal of the American College of Cardiology

2023/3/7

Zahra Azizi
Zahra Azizi

H-Index: 14

Ruibin Feng
Ruibin Feng

H-Index: 8

Segmenting computed tomograms for cardiac ablation using machine learning leveraged by domain knowledge encoding

Frontiers in cardiovascular medicine

2023

Novel Regional Analysis of Left Atrial Strain From Computed Tomography Separates Patients With Persistent versus Paroxysmal Atrial Fibrillation

Circulation

2023/11/7

Separating Patients With Long-Term Success versus Acute Response From Atrial Fibrillation Ablation Using Explainable Machine Learning

Circulation

2023/11/7

Ruibin Feng
Ruibin Feng

H-Index: 8

Optimizing ChatGPT to Detect VT Recurrence From Complex Medical Notes

Circulation

2023/11/7

Logic-Based Natural Language Processing Identifies VT Recurrence in the Electronic Health Record

Circulation

2023/11/7

Weakly-Supervised Deep Learning for Left Ventricle Fibrosis Segmentation in Cardiac MRI Using Image-Level Labels

2022/9/4

Ruibin Feng
Ruibin Feng

H-Index: 8

Sanjiv Narayan
Sanjiv Narayan

H-Index: 45

Systems, methods, and apparatuses for the generation of source models for transfer learning to application specific models used in the processing of medical imaging

2022/8/18

Novel Domain Knowledge Encoding Enables Machine Learning of Rapid, Expert-level Segmentation of Cardiac Computed Tomography

2022/8/10

Atrial fibrillation signatures on intracardiac electrograms identified by deep learning

Computers in biology and medicine

2022/6/1

Miguel Rodrigo
Miguel Rodrigo

H-Index: 12

Ruibin Feng
Ruibin Feng

H-Index: 8

See List of Professors in Ruibin Feng University(Arizona State University)