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ORCIDNandita Bhaskhar
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2020 – today
- 2024
[j2]Nandita Bhaskhar
, Daniel L. Rubin, Christopher Lee-Messer:
An Explainable and Actionable Mistrust Scoring Framework for Model Monitoring. IEEE Trans. Artif. Intell. 5(4): 1473-1485 (2024)- 2023
- [j1]Nandita Bhaskhar, Wui Ip, Jonathan H. Chen, Daniel L. Rubin:
Clinical outcome prediction using observational supervision with electronic health records and audit logs. J. Biomed. Informatics 147: 104522 (2023) - [c3]Rogier van der Sluijs, Nandita Bhaskhar, Daniel L. Rubin, Curtis P. Langlotz, Akshay S. Chaudhari:
Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays. MIDL 2023: 444-467 - [c2]Juanma Zambrano Chaves, Nandita Bhaskhar, Maayane Attias, Jean-Benoit Delbrouck, Daniel L. Rubin, Andreas M. Loening, Curtis P. Langlotz, Akshay Chaudhari:
RaLEs: a Benchmark for Radiology Language Evaluations. NeurIPS 2023 - [c1]Florian Dubost, Erin Hong, Siyi Tang, Nandita Bhaskhar, Christopher Lee-Messer, Daniel L. Rubin:
Semi-Supervised Learning for Sparsely-Labeled Sequential Data: Application to Healthcare Video Processing. WACV 2023: 1890-1899 - [i5]Rogier van der Sluijs, Nandita Bhaskhar, Daniel L. Rubin, Curtis P. Langlotz, Akshay Chaudhari:
Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays. CoRR abs/2301.12636 (2023) - 2022
- [i4]Nandita Bhaskhar, Daniel L. Rubin, Christopher Lee-Messer:
TRUST-LAPSE: An Explainable & Actionable Mistrust Scoring Framework for Model Monitoring. CoRR abs/2207.11290 (2022) - [i3]Jeffrey Dominic, Nandita Bhaskhar, Arjun D. Desai, Andrew M. Schmidt, Elka B. Rubin, Beliz Gunel, Garry E. Gold, Brian A. Hargreaves, Leon Lenchik, Robert Boutin, Akshay S. Chaudhari:
Data-Limited Tissue Segmentation using Inpainting-Based Self-Supervised Learning. CoRR abs/2210.07936 (2022) - 2021
- [i2]Florian Dubost, Khaled Kamal Saab, Erin Hong, Daniel Yang Fu, Max Pike, Siddharth Sharma, Siyi Tang, Nandita Bhaskhar, Christopher Lee-Messer, Daniel L. Rubin:
Double Descent Optimization Pattern and Aliasing: Caveats of Noisy Labels. CoRR abs/2106.02100 (2021) - 2020
- [i1]Florian Dubost, Erin Hong, Daniel Y. Fu, Nandita Bhaskhar, Siyi Tang, Khaled Saab, Daniel L. Rubin, Jared Dunnmon, Christopher Lee-Messer:
Let's Hope it Works! Inaccurate Supervision of Neural Networks with Incorrect Labels: Application to Epilepsy. CoRR abs/2011.14101 (2020)
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