Richard Cohan

University of Michigan

United States

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Articles (15)

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2024

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2024

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2024

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2020

Collaborators (6)

Nathaniel Meyer

University of Michigan

UNITED STATES

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Isaac Francis

University of Michigan–Ann Arbor

UNITED STATES

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Sean Woolen

Assistant Professor

UCSF Medical Center

UNITED STATES

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David Bloom

Clinial Professor of Radiology

Michigan Medicine

UNITED STATES

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Rohan Garje

Iowa State University

UNITED STATES

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Yousef Zakharia

The University of Iowa

UNITED STATES

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Richard Cohan

Research Interests

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Articles (15)

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A Survey of Practicing Radiologists on the Use of Premedication Before Intravenous Iodinated Contrast Medium Administration

Large language model-assisted information extraction from clinical reports for survival prediction of bladder cancer patients

A multi-institutional observer study of AI-aided oncologists' performance on treatment response assessment of bladder cancer.

Survival Prediction of Patients with Bladder Cancer after Cystectomy Based on Clinical, Radiomics, and Deep-Learning Descriptors

Computerized Decision Support for Bladder Cancer Treatment Response Assessment in CT Urography: Effect on Diagnostic Accuracy in Multi-Institution Multi-Specialty Study

Effect of computerized decision support on diagnostic accuracy and intra-observer variability in multi-institutional observer performance study for bladder cancer treatment response assessment in CT urography

Invited Commentary: Use of Bosniak Classification, Version 2019 in Clinical Practice.

Multi-institutional observer performance study for bladder cancer treatment response assessment in CT urography with and without computerized decision support

Cocaine Nephropathy: A Rare Cause of Abnormal Nephrograms.

Video Interviewing: A Review and Recommendations for Implementation in the Era of COVID-19 and Beyond

Intraobserver variability in bladder cancer treatment response assessment with and without computerized decision support

Bladder wall segmentation using U-net based deep learning

Convolutional neural networkbased decision support system for bladder cancer staging in CT urography: Decision threshold estimation and validation

Bladder Wall Segmentation using U-Net-based Deep-Learning.

Collaborators (6)

Nathaniel Meyer

Isaac Francis

Sean Woolen

David Bloom

Rohan Garje

Yousef Zakharia

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