no code implementations • 21 Jul 2021 • Imon Banerjee, Ananth Reddy Bhimireddy, John L. Burns, Leo Anthony Celi, Li-Ching Chen, Ramon Correa, Natalie Dullerud, Marzyeh Ghassemi, Shih-Cheng Huang, Po-Chih Kuo, Matthew P Lungren, Lyle Palmer, Brandon J Price, Saptarshi Purkayastha, Ayis Pyrros, Luke Oakden-Rayner, Chima Okechukwu, Laleh Seyyed-Kalantari, Hari Trivedi, Ryan Wang, Zachary Zaiman, Haoran Zhang, Judy W Gichoya
Methods: Using private and public datasets we evaluate: A) performance quantification of deep learning models to detect race from medical images, including the ability of these models to generalize to external environments and across multiple imaging modalities, B) assessment of possible confounding anatomic and phenotype population features, such as disease distribution and body habitus as predictors of race, and C) investigation into the underlying mechanism by which AI models can recognize race.
1 code implementation • NeurIPS 2017 • Toan Tran, Trung Pham, Gustavo Carneiro, Lyle Palmer, Ian Reid
Data augmentation is an essential part of the training process applied to deep learning models.
no code implementations • 1 Jul 2016 • Gustavo Carneiro, Luke Oakden-Rayner, Andrew P. Bradley, Jacinto Nascimento, Lyle Palmer
We propose new methods for the prediction of 5-year mortality in elderly individuals using chest computed tomography (CT).