Jasbir Dhaliwal

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Assistant Professor

Cincinnati Children's Hospital Medical Center

United States

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Dr. Jasbir Dhaliwal is an Assistant Professor at Cincinnati Children's Hospital Medical Center, located in the United States. His research focuses on the application of artificial intelligence and machine learning in the diagnosis and treatment of inflammatory bowel disease (IBD). Recent publications include studies on predictive models for pediatric ulcerative colitis and the incidence of IBD in diverse populations, particularly among South Asian and Chinese individuals. He is actively involved in initiatives aimed at improving therapeutic strategies for IBD management.

Recent Grants

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Leveraging Deep Learning to Delineate Histologic Features Predictive of Pediatric Ulcerative Colitis

Open Date: 2022-01-01

Close Date: 2024-12-31

Articles (13)

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2025

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2024

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2024

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2022

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2021

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2021

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2021

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2021

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2021

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2020

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2020

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2020

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2020

Collaborators (3)

Eileen Crowley

Western University

CANADA

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Surya Prasath

Assistant Professor

University of Cincinnati

UNITED STATES

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WAEL EL-MATARY

Professor

University of Manitoba

CANADA

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Jasbir Dhaliwal

Research Interests

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About

Recent Grants

Articles (13)

Automating Endoscopic Scoring Through Artificial Intelligence

Artificial intelligence image-based prediction models in IBD exhibit high risk of bias: A systematic review

Machine Learning–Based Prediction of Pediatric Ulcerative Colitis Treatment Response Using Diagnostic Histopathology

The Phenotypic Spectrum of New-onset IBD in Canadian Children of South Asian Ethnicity: A Prospective Multi-Centre Comparative Study

Incidence of Inflammatory Bowel Disease in South Asian and Chinese People: A Population-Based Cohort Study from Ontario, Canada

One-year outcomes with ustekinumab therapy in infliximab-refractory paediatric ulcerative colitis: a multicentre prospective study.

STRIDE-II: An Update on the Selecting Therapeutic Targets in Inflammatory Bowel Disease (STRIDE) Initiative of the International Organization for the Study of IBD (IOIBD): Determining Therapeutic Goals for Treat-to-Target strategies in IBD.

Predicting Therapeutic Response in Pediatric Ulcerative Colitis-A Journey Towards Precision Medicine.

Accurate Classification of Pediatric Colonic Inflammatory Bowel Disease Subtype Using a Random Forest Machine Learning Classifier

Accurate classification of pediatric colonic IBD subtype using a random forest machine learning classifier.

Body Composition Using Air Displacement Plethysmography in Children With Inflammatory Bowel Disease.

Body Composition Using Air Displacement Plethysmography in Children With Inflammatory Bowel Disease

Differentiation of Colonic IBD: Re-examination of PIBD Classes Algorithm With Resected Colon As Gold Standard.

Collaborators (3)

Eileen Crowley

Surya Prasath

WAEL EL-MATARY

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