no code implementations • 8 Feb 2022 • Jiwoong J. Jeong, Brianna L. Vey, Ananth Reddy, Thomas Kim, Thiago Santos, Ramon Correa, Raman Dutt, Marina Mosunjac, Gabriela Oprea-Ilies, Geoffrey Smith, Minjae Woo, Christopher R. McAdams, Mary S. Newell, Imon Banerjee, Judy Gichoya, Hari Trivedi
Developing and validating artificial intelligence models in medical imaging requires datasets that are large, granular, and diverse.
no code implementations • 8 May 2023 • Linglin Zhang, Beatrice Brown-Mulry, Vineela Nalla, InChan Hwang, Judy Wawira Gichoya, Aimilia Gastounioti, Imon Banerjee, Laleh Seyyed-Kalantari, Minjae Woo, Hari Trivedi
However, after controlling for confounding, we found lower FN risk associates with Other race(RR=0. 828;p=. 050), biopsy-proven benign lesions(RR=0. 927;p=. 011), and mass(RR=0. 921;p=. 010) or asymmetry(RR=0. 854;p=. 040); higher FN risk associates with architectural distortion (RR=1. 037;p<. 001).
1 code implementation • 8 Oct 2023 • InChan Hwang, Minjae Woo
This research presents a novel framework for the compression and decompression of medical images utilizing the Latent Diffusion Model (LDM).
no code implementations • 21 Nov 2023 • Carolina A. M. Heming, Mohamed Abdalla, Monish Ahluwalia, Linglin Zhang, Hari Trivedi, Minjae Woo, Benjamin Fine, Judy Wawira Gichoya, Leo Anthony Celi, Laleh Seyyed-Kalantari
Clinical AI model reporting cards should be expanded to incorporate a broad bias reporting of both social and non-social factors.