Jeroen van der Laak

About Jeroen van der Laak

Jeroen van der Laak, With an exceptional h-index of 55 and a recent h-index of 42 (since 2020), a distinguished researcher at Radboud Universiteit, specializes in the field of Digital Pathology, Computational Pathology, Deep Learning, Image Analysis.

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

Automatic data augmentation to improve generalization of deep learning in H&E stained histopathology

Uncertainty-guided annotation enhances segmentation with the human-in-the-loop

Image‐based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno‐oncology Biomarker Working Group on Breast Cancer

Full resolution reconstruction of whole-mount sections from digitized individual tissue fragments

Lymph node metastases and recurrence in pT1 colorectal cancer: Prediction with the International Budding Consortium Score—A retrospective, multi‐centric study

Multi-resolution deep learning characterizes tertiary lymphoid structures and their prognostic relevance in solid tumors

Deep learning detects premalignant lesions in the Fallopian tube

Masked attention as a mechanism for improving interpretability of Vision Transformers

Jeroen van der Laak Information

University

Position

Radboud University Medical Center

Citations(all)

26897

Citations(since 2020)

21997

Cited By

13599

hIndex(all)

55

hIndex(since 2020)

42

i10Index(all)

155

i10Index(since 2020)

115

Email

University Profile Page

Google Scholar

Jeroen van der Laak Skills & Research Interests

Digital Pathology

Computational Pathology

Deep Learning

Image Analysis

Top articles of Jeroen van der Laak

Automatic data augmentation to improve generalization of deep learning in H&E stained histopathology

Computers in Biology and Medicine

2024/3/1

Jeroen Van Der Laak
Jeroen Van Der Laak

H-Index: 33

Geert Litjens
Geert Litjens

H-Index: 11

Uncertainty-guided annotation enhances segmentation with the human-in-the-loop

arXiv preprint arXiv:2404.07208

2024/2/16

Full resolution reconstruction of whole-mount sections from digitized individual tissue fragments

Scientific Reports

2024/1/17

Lymph node metastases and recurrence in pT1 colorectal cancer: Prediction with the International Budding Consortium Score—A retrospective, multi‐centric study

United European gastroenterology journal

2024/1/9

Multi-resolution deep learning characterizes tertiary lymphoid structures and their prognostic relevance in solid tumors

Communications Medicine

2024/1/5

Deep learning detects premalignant lesions in the Fallopian tube

npj Women's Health

2024/4/29

Masked attention as a mechanism for improving interpretability of Vision Transformers

arXiv preprint arXiv:2404.18152

2024/4/28

Geert Litjens
Geert Litjens

H-Index: 11

Jeroen Van Der Laak
Jeroen Van Der Laak

H-Index: 33

Reply to:“Addressing Chatbots as Artificial Intelligence Aids in Pediatric Pathology”

Pediatric and Developmental Pathology

2024/4/14

Thomas De Bel
Thomas De Bel

H-Index: 5

Jeroen Van Der Laak
Jeroen Van Der Laak

H-Index: 33

Towards embedding stain-invariance in convolutional neural networks for H&E-stained histopathology

2024/4/3

Jeroen Van Der Laak
Jeroen Van Der Laak

H-Index: 33

Geert Litjens
Geert Litjens

H-Index: 11

Diffusion models for out-of-distribution detection in digital pathology

Medical Image Analysis

2024/4/1

Automated mitotic spindle hotspot counts are highly associated with clinical outcomes in systemically untreated early-stage triple-negative breast cancer

npj Breast Cancer

2024/3/29

Francesco Ciompi
Francesco Ciompi

H-Index: 24

Jeroen Van Der Laak
Jeroen Van Der Laak

H-Index: 33

Improving Quality Control of Whole Slide Images by Explicit Artifact Augmentation

2024/3/19

Jeroen Van Der Laak
Jeroen Van Der Laak

H-Index: 33

The Banff 2022 Kidney Meeting Work Plan: data-driven refinement of the Banff Classification for renal allografts

American journal of transplantation

2024/3/1

Uniform Noting for International application of the Tumor-stroma ratio as Easy Diagnostic tool: The UNITED study-An update

European Journal of Surgical Oncology

2023/2/1

Computational pathology in 2030: a Delphi study forecasting the role of AI in pathology within the next decade

EBioMedicine

2023/2/1

Banff Digital Pathology Working Group: Image Bank, Artificial Intelligence Algorithm, and Challenge Trial Developments

Transplant International

2023

Deep learning based tumor–stroma ratio scoring in colon cancer correlates with microscopic assessment

Journal of Pathology Informatics

2023/1/1

Corresponding E-mail address: jasper. linmans@ radboudumc. nl (J. Linmans).

MEDICAL IMAGE ANALYSIS

2023/1/1

See List of Professors in Jeroen van der Laak University(Radboud Universiteit)

Co-Authors

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