Eugene Shkolyar

Eugene Shkolyar

Stanford University

H-index: 10

North America-United States

About Eugene Shkolyar

Eugene Shkolyar, With an exceptional h-index of 10 and a recent h-index of 10 (since 2020), a distinguished researcher at Stanford University, specializes in the field of Urology.

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

MP71-19 ULTRASENSITIVE URINARY LIQUID BIOPSY ANALYSIS FOR BCG RESPONSE ASSESSMENT IN HIGH-RISK NON-MUSCLE INVASIVE BLADDER CANCER

PD30-03 PREDICTING RESPONSE TO INTRAVESICAL BCG IN HIGH RISK NON-MUSCLE INVASIVE BLADDER CANCER USING AN ARTIFICIAL INTELLIGENCE-POWERED PATHOLOGY ASSAY: DEVELOPMENT AND …

MP16-04 MINIMAL RESIDUAL DISEASE DETECTION SUPPORTS HIGH-GRADE BLADDER CANCER RISK-STRATIFICATION DURING RECOMMENDED REPEAT TRANSURETHRAL RESECTION

PD27-12 DEVELOPMENT AND VALIDATION OF GENERALIZABLE INTERPRETABLE AI BIOMARKERS TO PREDICT CLINICAL OUTCOMES IN BCG-TREATED PATIENTS WITH NON-MUSCLE INVASIVE BLADDER CANCER

A temporal correlation-driven AI model powered by large-scale clinical data for endoscopic detection of bladder tumors

Bladder Cancer and Artificial Intelligence: Emerging Applications

Genitourinary System

Efficient Augmented Intelligence Framework for Bladder Lesion Detection

Eugene Shkolyar Information

University

Position

___

Citations(all)

887

Citations(since 2020)

657

Cited By

459

hIndex(all)

10

hIndex(since 2020)

10

i10Index(all)

10

i10Index(since 2020)

10

Email

University Profile Page

Google Scholar

Eugene Shkolyar Skills & Research Interests

Urology

Top articles of Eugene Shkolyar

MP71-19 ULTRASENSITIVE URINARY LIQUID BIOPSY ANALYSIS FOR BCG RESPONSE ASSESSMENT IN HIGH-RISK NON-MUSCLE INVASIVE BLADDER CANCER

The Journal of Urology

2024/5

PD30-03 PREDICTING RESPONSE TO INTRAVESICAL BCG IN HIGH RISK NON-MUSCLE INVASIVE BLADDER CANCER USING AN ARTIFICIAL INTELLIGENCE-POWERED PATHOLOGY ASSAY: DEVELOPMENT AND …

The Journal of Urology

2024/5

MP16-04 MINIMAL RESIDUAL DISEASE DETECTION SUPPORTS HIGH-GRADE BLADDER CANCER RISK-STRATIFICATION DURING RECOMMENDED REPEAT TRANSURETHRAL RESECTION

The Journal of Urology

2024/5

Eugene Shkolyar
Eugene Shkolyar

H-Index: 6

PD27-12 DEVELOPMENT AND VALIDATION OF GENERALIZABLE INTERPRETABLE AI BIOMARKERS TO PREDICT CLINICAL OUTCOMES IN BCG-TREATED PATIENTS WITH NON-MUSCLE INVASIVE BLADDER CANCER

The Journal of Urology

2024/5

A temporal correlation-driven AI model powered by large-scale clinical data for endoscopic detection of bladder tumors

2024/3/13

Bladder Cancer and Artificial Intelligence: Emerging Applications

2024/2/1

Genitourinary System

RadTool Nuclear Medicine MCQs: Board Exam Preparation

2021

Efficient Augmented Intelligence Framework for Bladder Lesion Detection

JCO Clinical Cancer Informatics

2023/9

Tumor detection under cystoscopy with transformer-augmented deep learning algorithm

Physics in Medicine & Biology

2023/8/7

Real-time detection of bladder cancer using augmented cystoscopy with deep learning: a pilot study

Journal of Endourology

2023/7/11

Laying the Groundwork for Optimized Surgical Feedback

JAMA Network Open

2023/6/1

Eugene Shkolyar
Eugene Shkolyar

H-Index: 6

Conceptual framework and documentation standards of cystoscopic media content for artificial intelligence

Journal of Biomedical Informatics

2023/6/1

Corrigendum to “1773P Prediction of chemotherapy response in muscle-invasive bladder cancer: A machine learning approach”:[Annals of Oncology 32 (2022) S1348]

Annals of Oncology

2023/5/1

PD01-09 A TRANSFORMER-AUGMENTED DEEP LEARNING ALGORITHM, CYSTONET-T, FOR IMPROVED CYSTOSCOPIC BLADDER CANCER DETECTION

The Journal of Urology

2023/4

MP60-18 EFFICIENT AUGMENTED INTELLIGENCE STRATEGY WITH POTENTIAL USE FOR REAL-TIME BLADDER TUMOR DETECTION

The Journal of Urology

2023/4

MP63-02 PROSPECTIVE MULTI-INSTITUTIONAL VALIDATION OF a 3-GENE mRNA BIOMARKER PANEL FOR DETECTION AND SURVEILLANCE OF NON-MUSCLE INVASIVE BLADDER CANCER

The Journal of Urology

2023/4

Eugene Shkolyar
Eugene Shkolyar

H-Index: 6

PD01-12 DEEP LEARNING AUGMENTED DETECTION OF FLAT LESIONS ON WHITE LIGHT CYSTOSCOPY

The Journal of Urology

2023/4

Flat lesion detection of white light cystoscopy with deep learning

2023/3/14

Sequential modeling for cystoscopic image classification

2023/3/14

An Efficient Framework for Video Documentation of Bladder Lesions for Cystoscopy: A Proof-of-Concept Study

Journal of medical systems

2022/10/3

See List of Professors in Eugene Shkolyar University(Stanford University)