Brandon D. Gallas

United States Food and Drug Administration — United States

Computer Science · Physical Sciences

27h-index4.1kcitations116works3.22yr avg
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Research Topics

AI in cancer detection(32), Digital Radiography and Breast Imaging(21), Radiomics and Machine Learning in Medical Imaging(21), Medical Imaging Techniques and Applications(15), Cell Image Analysis Techniques(14)

Publications115 total

Abstract P2-02-18: Agreement Across 10 Artificial Intelligence Models in Assessing HER2 in Breast Cancer Whole Slide Images: Findings from the Friends of Cancer Research Digital PATH Project
Clinical Cancer Research·2025· 1 cited
Medical Imaging Data Strategies for Catalyzing AI Medical Device Innovation
Journal of Imaging Informatics in Medicine·2025· 1 citedOpen Access
Prioritizing cases from a multi-institutional cohort for a dataset of pathologist annotations
Journal of Pathology Informatics·2024Open Access
Assessment of machine learning algorithms for TILs scoring using whole slide images: comparison with pathologists
2024· 2 cited
Training pathologists to assess stromal tumour‐infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research
Histopathology·2024· 7 citedOpen Access
Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models
Modern Pathology·2024· 8 citedOpen Access
Expanding to Arbitrary Study Designs: ANOVA to Estimate Limits of Agreement for MRMC Studies
arXiv (Cornell University)·2023Open Access
Initial interactions with the <scp>FDA</scp> on developing a validation dataset as a medical device development tool
The Journal of Pathology·2023· 2 citedOpen Access
Regulatory considerations for medical imaging AI/ML devices in the United States: concepts and challenges
Journal of Medical Imaging·2023· 28 citedOpen Access
Effect of color-normalization on deep learning segmentation models for tumor-infiltrating lymphocytes scoring using breast cancer histopathology images
2023· 3 cited
Analysis of a pilot study collecting pathologist annotations for validating machine learning algorithms
2023· 1 cited
Abstract P1-08-05: Educating pathologists in quantitating stromal tumor-infiltrating lymphocytes in breast cancer for artificial intelligence applications
Cancer Research·2023
Single reader between-cases AUC estimator with nested data
Statistical Methods in Medical Research·2022Open Access
Pilot study to evaluate tools to collect pathologist annotations for validating machine learning algorithms
Journal of Medical Imaging·2022· 6 citedOpen Access
Development of Training Materials for Pathologists to Provide Machine Learning Validation Data of Tumor-Infiltrating Lymphocytes in Breast Cancer
Cancers·2022· 13 citedOpen Access
Three-Way Mixed Effect ANOVA to Estimate MRMC Limits of Agreement
Statistics in Biopharmaceutical Research·2022· 2 citedOpen Access
FDA fosters innovative approaches in research, resources and collaboration
Nature Machine Intelligence·2022· 6 citedOpen Access
Three-Way Mixed Effect ANOVA to Estimate MRMC Limits of Agreement
Figshare·2022Open Access
Advancing Research on Medical Image Perception by Strengthening Multidisciplinary Collaboration
JNCI Cancer Spectrum·2021· 8 citedOpen Access
Three-way Mixed Effect ANOVA to Estimate MRMC Limits of Agreement
arXiv (Cornell University)·2021Open Access
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Frequent Co-authors

Kyle J. Myers(15), Aldo Badano(12), Weijie Chen(8), Nicholas Petrick(8), Stephen M. Hewitt(8), W. Fraser Symmans(6), F. W. Samuelson(6), Berkman Sahiner(6), Matthew G. Hanna(5), Lajos Pusztai(4), Gene Pennello(4), Stefan Michiels(4), Sylvia Adams(4), Giuseppe Viale(4), Sunil Badve(4), Christos Sotiriou(4), David L. Rimm(4), Carsten Denkert(4), Sibylle Loibl(4), Giancarlo Pruneri(4)