AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing. - Katikapalli Subramanyam Kalyan; Ajit Rajasekharan; Sivanesan Sangeetha (CoRR, 2021)

Building a best-in-class automated de-identification tool for electronic health records through ensemble learning. - Karthik Murugadoss; Ajit Rajasekharan; Bradley A. Malin; Vineet Agarwal; Sairam Bade; Jeff R. Anderson; Jason L. Ross; William A. Faubion Jr.; John D. Halamka; Venky Soundararajan; Sankar Ardhanari (Patterns, 2021)

AMMU: A survey of transformer-based biomedical pretrained language models. - Katikapalli Subramanyam Kalyan; Ajit Rajasekharan; Sivanesan Sangeetha (J. Biomed. Informatics, 2022)

HypUC: Hyperfine Uncertainty Calibration with Gradient- boosted Corrections for Reliable Regression on Imbalanced Electrocardiograms. - Uddeshya Upadhyay; Sairam Bade; Arjun Puranik; Shahir Asfahan; Melwin Babu; Francisco Lopez-Jimenez; Samuel J. Asirvatham; Ashim Prasad; Ajit Rajasekharan; Samir Awasthi; Rakesh Barve (Trans. Mach. Learn. Res., 2023)