When is a Foundation Model a Foundation Model

Review of the current state of whole slide imaging in pathology

Liron Pantanowitz, Paul N Valenstein, Andrew J Evans, Keith J Kaplan, John D Pfeifer, David C Wilbur, Laura C Collins, and Terence J Colgan · 2011

Earlier work this paper cites.

Yottixel–an image search engine for large archives of histopathology whole slide images

Shivam Kalra, Hamid R Tizhoosh, Charles Choi, Sultaan Shah, Phedias Diamandis, Clinton JV Campbell, and Liron Pantanowitz · 2020

Earlier work this paper cites.

Pan-cancer diagnostic consensus through searching archival histopathology images using artificial intelligence

Shivam Kalra, Hamid R Tizhoosh, Sultaan Shah, Charles Choi, Savvas Damaskinos, Amir Safarpoor, Sobhan Shafiei, et al · 2020

Earlier work this paper cites.

Fine-tuning and training of densenet for histopathology image representation using tcga diagnostic slides

Abtin Riasatian, Morteza Babaie, Danial Maleki, Shivam Kalra, Mojtaba Valipour, Sobhan Hemati, Manit Zaveri, et al · 2021

Earlier work this paper cites.

On the opportunities and risks of foundation models

Original

Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, et al · 2021

Earlier work this paper cites.

Learning transferable visual models from natural language supervision

Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, et al · 2021

Cited alongside, same era.

Emergent abilities of large language models

Original

Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, et al · 2022

Cited alongside, same era.

Integrating digital pathology into clinical practice

Matthew G Hanna, Orly Ardon, Victor E Reuter, Sahussapont Joseph Sirintrapun, Christine England, David S Klimstra, and Meera R Hameed · 2022

Cited alongside, same era.

The future of artificial intelligence in digital pathology–results of a survey across stakeholder groups

Céline N Heinz, Amelie Echle, Sebastian Foersch, Andrey Bychkov, and Jakob Nikolas Kather · 2022

Cited alongside, same era.

On the challenges and perspectives of foundation models for medical image analysis

Original

Shaoting Zhang and Dimitris Metaxas · 2023

Closest in time.

A visual–language foundation model for pathology image analysis using medical twitter

Zhi Huang, Federico Bianchi, Mert Yuksekgonul, Thomas J Montine, and James Zou · 2023

Closest in time.

Large-scale domain-specific pretraining for biomedical vision-language processing

Original

Sheng Zhang, Yanbo Xu, Naoto Usuyama, Jaspreet Bagga, Robert Tinn, Sam Preston, Rajesh Rao, et al · 2023

Closest in time.

Benchmarking self-supervised learning on diverse pathology datasets

Mingu Kang, Heon Song, Seonwook Park, Donggeun Yoo, and Sérgio Pereira · 2023

Closest in time.