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Market
Which pathology foundation model will be most cited in academic papers by end of 2024?
2
Resolution / Starting Odds
UNI • 25%
Virchow • 25%
Prov-GigaPath • 25%
Other • 25%
Academic citation databases like Google Scholar or PubMed
Story
Dana-Farber and Weill Cornell Develop AI Tools to Enhance Digital Pathology
Jul 11, 2024, 07:13 AM
Scientists from Dana-Farber Cancer Institute and Weill Cornell Medicine have developed new artificial intelligence (AI) tools tailored to digital pathology. These tools utilize high-resolution digital images created from tissue samples to help diagnose diseases and guide treatment. The collaboration aims to enhance diagnostic precision and efficiency through AI-pathologist synergy. Researchers, including Gabrielle Campanella and Thomas Fuchs from Icahn School of Medicine at Mount Sinai, have benchmarked eight pathology foundation models, such as UNI, Virchow, and Prov-GigaPath, on large-scale datasets for clinical diagnosis and biomarker discovery. The project also involves MohamedOmarMD, renato_umeton, and TheLancet. Additionally, a digital pathology framework called nuclei has been developed to further boost diagnostic accuracies. This development is part of a growing field that leverages AI to improve healthcare outcomes.
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