61 citations · 121 across the 9 of their papers we have counts for
10 papers
Towards trustworthy seizure onset detection using workflow notes
Khaled Saab, Siyi Tang, Mohamed Taha +3
A major barrier to deploying healthcare AI models is their trustworthiness. One form of trustworthiness is a model's robustness across different subgroups: while existing models ma…
Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space Models
Siyi Tang, Jared A. Dunnmon, Liangqiong Qu +4
Multivariate biosignals are prevalent in many medical domains, such as electroencephalography, polysomnography, and electrocardiography. Modeling spatiotemporal dependencies in mul…
ATCON: Attention Consistency for Vision Models
Ali Mirzazadeh, Florian Dubost, Maxwell Pike +4
Attention--or attribution--maps methods are methods designed to highlight regions of the model's input that were discriminative for its predictions. However, different attention ma…
TRUST-LAPSE: An Explainable and Actionable Mistrust Scoring Framework for Model Monitoring
Nandita Bhaskhar, Daniel L. Rubin, Christopher Lee-Messer
Continuous monitoring of trained ML models to determine when their predictions should and should not be trusted is essential for their safe deployment. Such a framework ought to be…
Domino: Discovering Systematic Errors with Cross-Modal Embeddings
Sabri Eyuboglu, Maya Varma, Khaled Saab +5
Machine learning models that achieve high overall accuracy often make systematic errors on important subsets (or slices) of data. Identifying underperforming slices is particularly…
Automated Detection of Patients in Hospital Video Recordings
Siddharth Sharma, Florian Dubost, Christopher Lee-Messer +1
In a clinical setting, epilepsy patients are monitored via video electroencephalogram (EEG) tests. A video EEG records what the patient experiences on videotape while an EEG device…