Karandeep Singh

Assistant Professor

University of Michigan

United States

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Karandeep Singh is an Assistant Professor at the University of Michigan, USA. His research focuses on the intersection of artificial intelligence and healthcare, particularly in the areas of racial bias detection in health datasets, clinical prediction models, and the implementation of AI in health systems. Recent publications emphasize the importance of fairness metrics in clinical risk predictions and the evaluation of AI-driven healthcare technologies.

Articles (19)

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2025

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Collaborators (9)

Fan Bu

Assistant Professor

University of Michigan School of Public Health

UNITED STATES

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Bhramar Mukherjee

UNITED STATES

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V.G.Vinod Vydiswaran

Associate Professor

University of Michigan

UNITED STATES

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Jorge Cerda

Albany Medical College

UNITED STATES

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W. Nicholson Price II

University of Michigan

UNITED STATES

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Christopher Longhurst

Clinical Professor

University of California, San Diego

UNITED STATES

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Lillian Rountree

University of Michigan–Ann Arbor

UNITED STATES

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Philip Payne

Janet and Bernard Becker Professor and Director

Washington University in St. Louis

UNITED STATES

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Genevieve Melton-Meaux

University of Minnesota

UNITED STATES

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Karandeep Singh

Research Interests

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About

Articles (19)

Reporting of Fairness Metrics in Clinical Risk Prediction Models Used for Precision Health: Scoping Review

Detecting, Characterizing, and Mitigating Implicit and Explicit Racial Biases in Health Care Datasets With Subgroup Learnability: Algorithm Development and Validation Study

Challenges in the Postmarket Surveillance of Clinical Prediction Models

Not All Clinical AI Monitoring Systems Are Created Equal: Review and Recommendations

Meeting the Artificial Intelligence Needs of U.S. Health Systems

A Call for Artificial Intelligence Implementation Science Centers to Evaluate Clinical Effectiveness

The Chief Health AI Officer — An Emerging Role for an Emerging Technology

Comparison of Auscultation Quality Using Contemporary Digital Stethoscopes

Evaluation of Sepsis Prediction Models before Onset of Treatment

Development of a decentralized cohort for studying post-acute sequelae of COVID-19 in India in the Data4life Study

Enabling collaborative governance of medical AI

Development and Validation of a Model to Predict Ureteral Stent Placement Following Ureteroscopy: Results from a Statewide Collaborative

Risk Prediction and Machine Learning

Artificial Intelligence Systems in CKD: Where Do We Stand and What Will the Future Bring?

Predicting persistent opioid use after surgery using electronic health record and patient-reported data

Preoperative Prostate MRI Predictors of Urinary Continence Following Radical Prostatectomy

External Validation of Postpartum Hemorrhage Prediction Models Using Electronic Health Record Data

Artificial Intelligence for AKI!Now: Let’s Not Await Plato’s Utopian Republic

Evaluating a Widely Implemented Proprietary Deterioration Index Model among Hospitalized Patients with COVID-19

Collaborators (9)

Fan Bu

Bhramar Mukherjee

V.G.Vinod Vydiswaran

Jorge Cerda

W. Nicholson Price II

Christopher Longhurst

Lillian Rountree

Philip Payne

Genevieve Melton-Meaux

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