1 code implementation • 27 May 2022 • Melanie Bernhardt, Fabio De Sousa Ribeiro, Ben Glocker
Failure detection in automated image classification is a critical safeguard for clinical deployment.
1 code implementation • 27 Oct 2021 • Ben Glocker, Charles Jones, Melanie Bernhardt, Stefan Winzeck
We explore test set resampling, transfer learning, multitask learning, and model inspection to assess the relationship between the encoding of protected characteristics and disease detection performance across subgroups.
1 code implementation • 1 Sep 2021 • Melanie Bernhardt, Daniel C. Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
Imperfections in data annotation, known as label noise, are detrimental to the training of machine learning models and have an often-overlooked confounding effect on the assessment of model performance.
1 code implementation • 14 Jul 2021 • Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel C. Castro
Chest radiography has been a recommended procedure for patient triaging and resource management in intensive care units (ICUs) throughout the COVID-19 pandemic.
no code implementations • 25 Jun 2020 • Melanie Bernhardt, Valery Vishnevskiy, Richard Rau, Orcun Goksel
In this work, we present for the first time a VN solution for a pulse-echo SoS image reconstruction problem using diverging waves with conventional transducers and single-sided tissue access.