Constance Lehman

Professor

MGH Institute of Health Professions

United States

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About

Constance Lehman is a Professor at the MGH Institute of Health Professions in the United States. Her research focuses on breast cancer detection and screening methodologies, with recent publications examining the efficacy of AI in screening mammography and various breast cancer risk models. She has also investigated aspects related to COVID-19's impact on imaging practices and the use of innovative localization techniques for nonpalpable breast lesions.

Articles (12)

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2024

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2024

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2023

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2023

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2022

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2022

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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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2020

Collaborators (7)

Fredrik Strand

Karolinska University Hospital

SWEDEN

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Imon Banerjee

Associate Professor

Mayo Clinic

UNITED STATES

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Anne Marie McCarthy

Assistant Professor

University of Pennsylvania

UNITED STATES

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Jung Hyun Yoon

Yonsei University

SOUTH KOREA

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Seema Khan

Professor

Northwestern University Feinberg School of Medicine

UNITED STATES

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Ilana Gareen

Brown University

UNITED STATES

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Pascal A. T. Baltzer

AUSTRIA

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Constance Lehman

Research Interests

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Articles (12)

Incidence, Timing, and Long-Term Outcomes of COVID-19 Vaccine-Related Lymphadenopathy on Screening Mammography

Missed Screening Mammography Appointments: Patient Sociodemographic Characteristics and Mammography Completion After 1 Year

Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis

Comparison of the Diagnostic Accuracy of Mammogram-based Deep Learning and Traditional Breast Cancer Risk Models in Patients Who Underwent Supplemental Screening with MRI

Multi-Institutional Validation of a Mammography-Based Breast Cancer Risk Model

Deep Learning vs Traditional Breast Cancer Risk Models to Support Risk-Based Mammography Screening

Magnetic Seeds: An Alternative to Wire Localization for Nonpalpable Breast Lesions

Preoperative Breast MRI for Newly Diagnosed Ductal Carcinoma in Situ: Imaging Features and Performance in a Multicenter Setting (ECOG-ACRIN E4112 Trial)

Toward robust mammography-based models for breast cancer risk

Stargazing through the lens of AI in clinical oncology

Imaging Surveillance of Breast Cancer Survivors with Digital Mammography versus Digital Breast Tomosynthesis

Breast Cancer Screening with Digital Breast Tomosynthesis: Are Initial Benefits Sustained?

Collaborators (7)

Fredrik Strand

Imon Banerjee

Anne Marie McCarthy

Jung Hyun Yoon

Seema Khan

Ilana Gareen

Pascal A. T. Baltzer

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