Deepta Rajan
Deepta Rajan
IBM Research AI
Verified email at asu.edu
Title
Cited by
Cited by
Year
Attend and diagnose: Clinical time series analysis using attention models
H Song, D Rajan, J Thiagarajan, A Spanias
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
1472018
Assessing individual performance in Agile undergraduate software engineering teams
RF Gamble, ML Hale
2013 IEEE Frontiers in Education Conference (FIE), 1678-1684, 2013
242013
Health monitoring laboratories by interfacing physiological sensors to mobile android devices
D Rajan, A Spanias, S Ranganath, MK Banavar, P Spanias
2013 IEEE Frontiers in Education Conference (FIE), 1049-1055, 2013
192013
A generative modeling approach to limited channel ECG classification
D Rajan, JJ Thiagarajan
2018 40th Annual International Conference of the IEEE Engineering in …, 2018
162018
Kernel sparse models for automated tumor segmentation
JJ Thiagarajan, KN Ramamurthy, D Rajan, A Spanias, A Puri, D Frakes
International Journal on Artificial Intelligence Tools 23 (03), 1460004, 2014
162014
Medical sieve: a cognitive assistant for radiologists and cardiologists
T Syeda-Mahmood, E Walach, D Beymer, F Gilboa-Solomon, M Moradi, ...
Medical Imaging 2016: Computer-Aided Diagnosis 9785, 97850A, 2016
102016
Embedding Android signal processing apps in a high school math class—An RET project
MK Banavar, D Rajan, A Strom, P Spanias, XS Zhang, H Braun, ...
2014 IEEE Frontiers in Education Conference (FIE) Proceedings, 1-4, 2014
102014
Understanding Behavior of Clinical Models under Domain Shifts
JJ Thiagarajan, D Rajan, P Sattigeri
arXiv preprint arXiv:1809.07806, 2018
9*2018
Leveraging medical visual question answering with supporting facts
T Kornuta, D Rajan, C Shivade, A Asseman, AS Ozcan
arXiv preprint arXiv:1905.12008, 2019
82019
Calibrating healthcare ai: Towards reliable and interpretable deep predictive models
JJ Thiagarajan, P Sattigeri, D Rajan, B Venkatesh
arXiv preprint arXiv:2004.14480, 2020
52020
Identifying patients at risk for aortic stenosis through learning from multimodal data
T Syeda-Mahmood, Y Guo, M Moradi, D Beymer, D Rajan, Y Cao, Y Gur, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2016
52016
Automated tumor segmentation using kernel sparse representations
JJ Thiagarajan, D Rajan, KN Ramamurthy, D Frakes, A Spanias
2012 IEEE 12th International Conference on Bioinformatics & Bioengineering …, 2012
52012
Pi-PE: A Pipeline for Pulmonary Embolism Detection using Sparsely Annotated 3D CT Images
D Rajan, D Beymer, S Abedin, E Dehghan
Machine Learning for Health Workshop, 220-232, 2020
42020
Generalization studies of neural network models for cardiac disease detection using limited channel ECG
D Rajan, D Beymer, G Narayan
2018 Computing in Cardiology Conference (CinC) 45, 1-4, 2018
42018
On the role of artificial intelligence in medical imaging of covid-19
J Born, D Beymer, D Rajan, A Coy, VV Mukherjee, M Manica, P Prasanna, ...
medRxiv, 2020.09. 02.20187096, 2021
32021
Improving Reliability of Clinical Models Using Prediction Calibration
JJ Thiagarajan, B Venkatesh, D Rajan, P Sattigeri
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and …, 2020
32020
Self-training with improved regularization for few-shot chest x-ray classification
D Rajan, JJ Thiagarajan, A Karargyris, S Kashyap
arXiv preprint arXiv:2005.02231, 2020
32020
Development of mobile sensing apps for DSP applications
D Rajan, G Kalyanasundaram, S Hu, M Banavar, A Spanias
2013 IEEE Digital Signal Processing and Signal Processing Education Meeting …, 2013
32013
Automatic Diagnosis of Pulmonary Embolism Using an Attention-guided Framework: A Large-scale Study
L Shi, D Rajan, S Abedin, MS Yellapragada, D Beymer, E Dehghan
Medical Imaging with Deep Learning, 743-754, 2020
22020
Learn-by-calibrating: using calibration as a training objective
JJ Thiagarajan, B Venkatesh, D Rajan
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
22020
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