most citedWhen is a Foundation Model a Foundation Model

6 citations · 6 across the 4 of their papers we have counts for

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8 papers

eess.IV2024

SPLICE -- Streamlining Digital Pathology Image Processing

Areej Alsaafin, Peyman Nejat, Abubakr Shafique +4

Digital pathology and the integration of artificial intelligence (AI) models have revolutionized histopathology, opening new opportunities. With the increasing availability of Whol…

eess.IV2024

Analysis and Validation of Image Search Engines in Histopathology

Isaiah Lahr, Saghir Alfasly, Peyman Nejat +16

Searching for similar images in archives of histology and histopathology images is a crucial task that may aid in patient matching for various purposes, ranging from triaging and d…

cs.CV2023

Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer: A systematic review

Ricardo Gonzalez, Peyman Nejat, Ashirbani Saha +3

Numerous machine learning (ML) models have been developed for breast cancer using various types of data. Successful external validation (EV) of ML models is important evidence of t…

cs.CV2023

Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities

Ricardo Gonzalez, Ashirbani Saha, Clinton J. V. Campbell +3

This paper discusses some overlooked challenges faced when working with machine learning models for histopathology and presents a novel opportunity to support "Learning Health Syst…

cs.CV2023

Selection of Distinct Morphologies to Divide & Conquer Gigapixel Pathology Images

Abubakr Shafique, Saghir Alfasly, Areej Alsaafin +3

Whole slide images (WSIs) are massive digital pathology files illustrating intricate tissue structures. Selecting a small, representative subset of patches from each WSI is essenti…

cs.CV2023

Rotation-Agnostic Image Representation Learning for Digital Pathology

Saghir Alfasly, Abubakr Shafique, Peyman Nejat +4

This paper addresses complex challenges in histopathological image analysis through three key contributions. Firstly, it introduces a fast patch selection method, FPS, for whole-sl…