Sarah M. Hooper

According to our database, Sarah M. Hooper authored at least 8 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

A case for reframing automated medical image classification as segmentation.

Sarah M. Hooper, Mayee F. Chen, Khaled Saab, Kush Bhatia, Curtis P. Langlotz, Christopher Ré

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data.

Maya Varma, Jean-Benoit Delbrouck, Sarah M. Hooper, Akshay Chaudhari, Curtis P. Langlotz

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Reducing Reliance on Spurious Features in Medical Image Classification with Spatial Specificity.

Khaled Saab, Sarah M. Hooper, Mayee F. Chen, Michael Zhang, Daniel L. Rubin, Christopher Ré

Proceedings of the Machine Learning for Healthcare Conference, 2022

Multi-tracer PET Imaging Using Deep Learning: Applications in Patients with High-Grade Gliomas.

Mirwais Wardak, Sarah M. Hooper, Christiaan Schiepers, Wei Chen, Carina Mari Aparici, Guido A. Davidzon, Ophir Vermesh, Timothy F. Cloughesy, Sung-Cheng Huang, Sanjiv Sam Gambhir

Proceedings of the Predictive Intelligence in Medicine - 5th International Workshop, 2022

2021

Observational Supervision for Medical Image Classification Using Gaze Data.

Khaled Saab, Sarah M. Hooper, Nimit Sharad Sohoni, Jupinder Parmar, Brian Pogatchnik, Sen Wu, Jared A. Dunnmon, Hongyang R. Zhang, Daniel L. Rubin, Christopher Ré

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Cut out the annotator, keep the cutout: better segmentation with weak supervision.

Sarah M. Hooper, Michael Wornow, Ying Hang Seah, Peter Kellman, Hui Xue, Frederic Sala, Curtis P. Langlotz, Christopher Ré

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Assessing Robustness to Noise: Low-Cost Head CT Triage.

Sarah M. Hooper, Jared A. Dunnmon, Matthew P. Lungren, Sanjiv Sam Gambhir, Christopher Ré, Adam S. Wang, Bhavik N. Patel

CoRR, 2020

Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods.

Daniel Y. Fu, Mayee F. Chen, Frederic Sala, Sarah M. Hooper, Kayvon Fatahalian, Christopher Ré

Proceedings of the 37th International Conference on Machine Learning, 2020