Tanuja Chitnis

According to our database, Tanuja Chitnis authored at least 11 papers between 2013 and 2026.

Collaborative distances:

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

2026

Reciprocal Co-Training (RCT): Coupling Gradient-Based and Non-Differentiable Models via Reinforcement Learning.

Yunshuo Tian, Akayou Kitessa, Tanuja Chitnis, Yijun Zhao

CoRR, April, 2026

2025

From Structured EHR Data to Narratives: Large Language Models for Early Prediction of Multiple Sclerosis Relapse.

Yijun Zhao, Evan Madill, Akayou A. Kitessa, Benjamin Castle, Aakruti R. Katre, Tanuja Chitnis

Proceedings of the IEEE International Conference on Data Mining, 2025

2022

Dirichlet Mixture of Gaussian Processes with Split-kernel: An Application to Predicting Disease Course in Multiple Sclerosis Patients.

Yijun Zhao, Tanuja Chitnis

Proceedings of the International Joint Conference on Neural Networks, 2022

2020

Ensemble learning predicts multiple sclerosis disease course in the SUMMIT study.

Yijun Zhao, Tong Wang, Riley Bove, Bruce Cree, Roland Henry, Hrishikesh Lokhande, Mariann Polgar-Turcsanyi, Mark Anderson, Rohit Bakshi, Howard L. Weiner, Tanuja Chitnis

npj Digit. Medicine, 2020

Author Correction: Ensemble learning predicts multiple sclerosis disease course in the SUMMIT study.

Yijun Zhao, Tong Wang, Riley Bove, Bruce Cree, Roland Henry, Hrishikesh Lokhande, Mariann Polgar-Turcsanyi, Mark Anderson, Rohit Bakshi, Howard L. Weiner, Tanuja Chitnis

npj Digit. Medicine, 2020

GRU-DF: A Temporal Model with Dynamic Imputation for Missing Target Values in Longitudinal Patient Data.

Yijun Zhao, Matias Berretta, Tong Wang, Tanuja Chitnis

Proceedings of the 8th IEEE International Conference on Healthcare Informatics, 2020

2019

Quantifying neurologic disease using biosensor measurements in-clinic and in free-living settings in multiple sclerosis.

Tanuja Chitnis, Bonnie I. Glanz, Cindy Gonzalez, Brian C. Healy, Taylor J. Saraceno, Neda Sattarnezhad, Camilo Diaz-Cruz, Mariann Polgar-Turcsanyi, Subhash Tummala, Rohit Bakshi, Vikram Bajaj, David Ben Shimol, Nikhil Bikhchandani, Alexander W. Blocker, Joshua Burkart, Raphael Cendrillon, Michael P. Cusack, Emre Demiralp, Sarel Kobus Jooste, Alaa Kharbouch, Amy A. Lee, Joseph Lehar, Manway Liu, Swaminathan Mahadevan, Mark Murphy, Linda C. Norton, Tushar Anil Parlikar, Anupam Pathak, Ali Shoeb, Erin Soderberg, Philip Stephens, Aaron H. Stoertz, Florence Thng, Kashyap R. Tumkur, Hongsheng Wang, Jane Rhodes, Richard A. Rudick, Richard M. Ransohoff, Glenn A. Phillips, Effie Bruzik, William J. Marks, Howard L. Weiner, Thomas M. Snyder

npj Digit. Medicine, 2019

2015

Using multiple imputation to efficiently correct cerebral MRI whole brain lesion and atrophy data in patients with multiple sclerosis.

Alicia S. Chua, Svetlana Egorova, Mark C. Anderson, Mariann Polgar-Turcsanyi, Tanuja Chitnis, Howard L. Weiner, Charles R. G. Guttmann, Rohit Bakshi, Brian C. Healy

NeuroImage, 2015

Domain Induced Dirichlet Mixture of Gaussian Processes: An Application to Predicting Disease Progression in Multiple Sclerosis Patients.

Yijun Zhao, Tanuja Chitnis, Brian C. Healy, Jennifer G. Dy, Carla E. Brodley

Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

2014

Addressing Human Subjectivity via Transfer Learning: An Application to Predicting Disease Outcome in Multiple Sclerosis Patients.

Yijun Zhao, Carla E. Brodley, Tanuja Chitnis, Brian C. Healy

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

2013

Removing Confounding Factors via Constraint Based Clustering: An Application to Finding Homogeneous Groups of Multiple Sclerosis Patients.

Jingjing Liu, Carla E. Brodley, Brian C. Healy, Tanuja Chitnis

Proceedings of the IEEE International Conference on Healthcare Informatics, 2013