Let's Hope it Works! Inaccurate Supervision of Neural Networks with Incorrect Labels: Application to Epilepsy. - Florian Dubost; Erin Hong; Daniel Y. Fu; Nandita Bhaskhar; Siyi Tang; Khaled Saab 002; Daniel L. Rubin; Jared Dunnmon; Christopher Lee-Messer (CoRR, 2020)

Weak supervision as an efficient approach for automated seizure detection in electroencephalography. - Khaled Saab 002; Jared Dunnmon; Christopher Ré; Daniel L. Rubin; Christopher Lee-Messer (npj Digit. Medicine, 2020)

Cross-Modal Data Programming Enables Rapid Medical Machine Learning. - Jared A. Dunnmon; Alexander J. Ratner; Khaled Saab 002; Nishith Khandwala; Matthew Markert; Hersh Sagreiya; Roger E. Goldman; Christopher Lee-Messer; Matthew P. Lungren; Daniel L. Rubin; Christopher Ré (Patterns, 2020)

Automated Seizure Detection and Seizure Type Classification From Electroencephalography With a Graph Neural Network and Self-Supervised Pre-Training. - Siyi Tang; Jared A. Dunnmon; Khaled Saab 002; Xuan Zhang; Qianying Huang; Florian Dubost; Daniel L. Rubin; Christopher Lee-Messer (CoRR, 2021)

Double Descent Optimization Pattern and Aliasing: Caveats of Noisy Labels. - Florian Dubost; Khaled Kamal Saab; Erin Hong; Daniel Yang Fu; Max Pike; Siddharth Sharma; Siyi Tang; Nandita Bhaskhar; Christopher Lee-Messer; Daniel L. Rubin (CoRR, 2021)

Automated Detection of Patients in Hospital Video Recordings. - Siddharth Sharma; Florian Dubost; Christopher Lee-Messer; Daniel L. Rubin (CoRR, 2021)

Domino: Discovering Systematic Errors with Cross-Modal Embeddings. - Sabri Eyuboglu; Maya Varma; Khaled Kamal Saab; Jean-Benoit Delbrouck; Christopher Lee-Messer; Jared Dunnmon; James Zou 001; Christopher Ré (ICLR, 2022)

Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis. - Siyi Tang; Jared Dunnmon; Khaled Kamal Saab; Xuan Zhang; Qianying Huang; Florian Dubost; Daniel L. Rubin; Christopher Lee-Messer (ICLR, 2022)

TRUST-LAPSE: An Explainable & Actionable Mistrust Scoring Framework for Model Monitoring. - Nandita Bhaskhar; Daniel L. Rubin; Christopher Lee-Messer (CoRR, 2022)

Spatiotemporal Modeling of Multivariate Signals With Graph Neural Networks and Structured State Space Models. - Siyi Tang; Jared A. Dunnmon; Liangqiong Qu; Khaled Kamal Saab; Christopher Lee-Messer; Daniel L. Rubin (CoRR, 2022)

Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space Models. - Siyi Tang; Jared A. Dunnmon; Liangqiong Qu; Khaled Kamal Saab; Tina Baykaner; Christopher Lee-Messer; Daniel L. Rubin (CHIL, 2023)

Semi-Supervised Learning for Sparsely-Labeled Sequential Data: Application to Healthcare Video Processing. - Florian Dubost; Erin Hong; Siyi Tang; Nandita Bhaskhar; Christopher Lee-Messer; Daniel L. Rubin (WACV, 2023)

ATCON: Attention Consistency for Vision Models. - Ali Mirzazadeh; Florian Dubost; Maxwell Pike; Krish Maniar; Max Zuo; Christopher Lee-Messer; Daniel L. Rubin (WACV, 2023)

bids-specification. - Aaron Oliver-Taylor; Adam Li; Adam G. Thomas; Adeen Flinker; Adina S. Wagner; Agah Karakuzu; Aki Nikolaidis; Alberto Lazari; Alejandro de la Vega; Alessio Giacomel; Alexander Rockhill; Alexander Jones; et al. (Zenodo, 2023)

Towards trustworthy seizure onset detection using workflow notes. - Khaled Saab 002; Siyi Tang; Mohamed Taha; Christopher Lee-Messer; Christopher Ré; Daniel L. Rubin (npj Digit. Medicine, 2024)

An Explainable and Actionable Mistrust Scoring Framework for Model Monitoring. - Nandita Bhaskhar; Daniel L. Rubin; Christopher Lee-Messer (IEEE Trans. Artif. Intell., 2024)

The Brain Imaging Data Structure (BIDS) Specification. - Aaron Oliver-Taylor; Adam Li; Adam G. Thomas; Adeen Flinker; Adina S. Wagner; Agah Karakuzu; Aki Nikolaidis; Alberto Lazari; Alejandro de la Vega; Alessio Giacomel; Alexander Rockhill; Alexander Jones; et al. (Zenodo, 2024)