Laura Heacock, MD, MS, FSBI

Laura Heacock, MD, MS, FSBI

New York University

H-index: 22

North America-United States

About Laura Heacock, MD, MS, FSBI

Laura Heacock, MD, MS, FSBI, With an exceptional h-index of 22 and a recent h-index of 20 (since 2020), a distinguished researcher at New York University, specializes in the field of Breast Cancer, Breast MRI, Machine learning, Artificial Intelligence.

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

PACS-integrated machine learning breast density classifier: clinical validation

An efficient deep neural network to classify large 3D images with small objects

Improving Information Extraction from Pathology Reports using Named Entity Recognition

Benchmd: A benchmark for modality-agnostic learning on medical images and sensors

Leveraging Transformers to Improve Breast Cancer Classification and Risk Assessment with Multi-modal and Longitudinal Data

Women 75 years old or older: to screen or not to screen?

Problem-solving Breast MRI

ChatGPT and other large language models are double-edged swords

Laura Heacock, MD, MS, FSBI Information

University

Position

Department of Radiology School of Medicine

Citations(all)

2974

Citations(since 2020)

2373

Cited By

1133

hIndex(all)

22

hIndex(since 2020)

20

i10Index(all)

31

i10Index(since 2020)

29

Email

University Profile Page

New York University

Google Scholar

View Google Scholar Profile

Laura Heacock, MD, MS, FSBI Skills & Research Interests

Breast Cancer

Breast MRI

Machine learning

Artificial Intelligence

Top articles of Laura Heacock, MD, MS, FSBI

Title

Journal

Author(s)

Publication Date

PACS-integrated machine learning breast density classifier: clinical validation

Clinical Imaging

John Lewin

Sven Schoenherr

Martin Seebass

MingDe Lin

Liane Philpotts

...

2023/9/1

An efficient deep neural network to classify large 3D images with small objects

IEEE Transactions on Medical Imaging

Jungkyu Park

Jakub Chłędowski

Stanisław Jastrzębski

Jan Witowski

Yanqi Xu

...

2023/8/17

Improving Information Extraction from Pathology Reports using Named Entity Recognition

Research Square

Ken G Zeng

Tarun Dutt

Jan Witowski

GV Kranthi Kiran

Frank Yeung

...

2023/7/3

Benchmd: A benchmark for modality-agnostic learning on medical images and sensors

arXiv preprint arXiv:2304.08486

Kathryn Wantlin

Chenwei Wu

Shih-Cheng Huang

Oishi Banerjee

Farah Dadabhoy

...

2023/4/17

Leveraging Transformers to Improve Breast Cancer Classification and Risk Assessment with Multi-modal and Longitudinal Data

arXiv preprint arXiv:2311.03217

Yiqiu Shen

Jungkyu Park

Frank Yeung

Eliana Goldberg

Laura Heacock

...

2023/11/6

Women 75 years old or older: to screen or not to screen?

Cindy S Lee

Alana Lewin

Beatriu Reig

Laura Heacock

Yiming Gao

...

2023/4/13

Problem-solving Breast MRI

Beatriu Reig

Eric Kim

Chloe M Chhor

Linda Moy

Alana A Lewin

...

2023/9/21

ChatGPT and other large language models are double-edged swords

Yiqiu Shen

Laura Heacock

Jonathan Elias

Keith D Hentel

Beatriu Reig

...

2023/1/26

New horizons: artificial intelligence for digital breast tomosynthesis

RadioGraphics

Julia E Goldberg

Beatriu Reig

Alana A Lewin

Yiming Gao

Laura Heacock

...

2022/11/4

Advances in abbreviated breast MRI and ultrafast imaging

Seminars in Roentgenology

Shalin Patel

Laura Heacock

Yiming Gao

Kristin Elias

Linda Moy

...

2022/4/1

An efficient deep neural network to find small objects in large 3D images

arXiv preprint arXiv:2210.08645

Jungkyu Park

Jakub Chłędowski

Stanisław Jastrzębski

Jan Witowski

Yanqi Xu

...

2022/10/16

Improving breast cancer diagnostics with deep learning for MRI

Science translational medicine

Jan Witowski

Laura Heacock

Beatriu Reig

Stella K Kang

Alana Lewin

...

2022/9/28

Biomarkers, Prognosis, and Prediction Factors

Beatriu Reig

Linda Moy

Eric E Sigmund

Laura Heacock

2022/6/18

Estimation of the capillary level input function for dynamic contrast‐enhanced MRI of the breast using a deep learning approach

Magnetic resonance in medicine

Jonghyun Bae

Zhengnan Huang

Florian Knoll

Krzysztof Geras

Terlika Pandit Sood

...

2022/5

Differences between human and machine perception in medical diagnosis

Scientific reports

Taro Makino

Stanisław Jastrzębski

Witold Oleszkiewicz

Celin Chacko

Robin Ehrenpreis

...

2022/4/27

A Simulation Pipeline to Generate Realistic Breast Images for Learning DCE-MRI Reconstruction

Zhengnan Huang

Jonghyun Bae

Patricia M Johnson

Terlika Sood

Laura Heacock

...

2021

Lessons from the first DBTex Challenge

Nature Machine Intelligence

Jungkyu Park

Yoel Shoshan

Robert Martí

Pablo Gómez del Campo

Vadim Ratner

...

2021/8

Abbreviated MR imaging for breast cancer

Laura Heacock

Alana A Lewin

Hildegard K Toth

Linda Moy

Beatriu Reig

2021/1/1

Breast MRI for evaluation of response to neoadjuvant therapy

Radiographics

Beatriu Reig

Alana A Lewin

Linda Du

Laura Heacock

Hildegard K Toth

...

2021/5

Magnetic resonance imaging in screening of breast cancer

Yiming Gao

Beatriu Reig

Laura Heacock

Debbie L Bennett

Samantha L Heller

...

2021/1/1

See List of Professors in Laura Heacock, MD, MS, FSBI University(New York University)

Co-Authors

H-index: 98
Kyunghyun Cho

Kyunghyun Cho

New York University

H-index: 76
Nico Karssemeijer

Nico Karssemeijer

Radboud Universiteit

H-index: 55
Ritse Mann

Ritse Mann

Radboud Universiteit

H-index: 41
Christopher G. Filippi

Christopher G. Filippi

Tufts University

H-index: 38
Robert D. Boutin

Robert D. Boutin

Stanford University

H-index: 27
Ashley Weaver, PhD

Ashley Weaver, PhD

Wake Forest University

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