Todd J. Schwedt

According to our database, Todd J. Schwedt authored at least 7 papers between 2021 and 2025.

Collaborative distances:

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

2025

MAGIC: Multi-task Gaussian process for joint imputation and classification in healthcare time series.

Dohyun Ku, Catherine D. Chong, Visar Berisha, Todd J. Schwedt, Jing Li

CoRR, September, 2025

DinoAtten3D: Slice-Level Attention Aggregation of DinoV2 for 3D Brain MRI Anomaly Classification.

Fazle Rafsani, Jay Shah, Catherine D. Chong, Todd J. Schwedt, Teresa Wu

CoRR, September, 2025

2024

Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR Images.

Md Mahfuzur Rahman Siddiquee, Jay Shah, Teresa Wu, Catherine D. Chong, Todd J. Schwedt, Gina Dumkrieger, Simona Nikolova, Baoxin Li

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Multi-modal Predictive Model for MACE Risk Estimation in Patients with Migraine.

Amara Tariq, Oana M. Dumitrascu, Man Luo, Gina Dumkrieger, Todd J. Schwedt, Catherine D. Chong, Imon Banerjee

Proceedings of the 12th IEEE International Conference on Healthcare Informatics, 2024

2022

Generalizable Natural Language Processing Framework for Migraine Reporting from Social Media.

Yuting Guo, Swati Rajwal, Sahithi Lakamana, Chia-Chun Chiang, Paul C. Menell, Adnan H. Shahid, Yi-Chieh Chen, Nikita Chhabra, Wan-Ju Chao, Chieh-Ju Chao, Todd J. Schwedt, Imon Banerjee, Abeed Sarker

CoRR, 2022

HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human Disease.

Md Mahfuzur Rahman Siddiquee, Jay Shah, Teresa Wu, Catherine D. Chong, Todd J. Schwedt, Baoxin Li

Proceedings of the Simulation and Synthesis in Medical Imaging, 2022

2021

A novel hierarchically-structured factor mixture model for cluster discovery from multi-modality data.

Bing Si, Todd J. Schwedt, Catherine D. Chong, Teresa Wu, Jing Li

IISE Trans., 2021