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Deepta Rajan
Deepta Rajan
Microsoft
Zweryfikowany adres z asu.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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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
4812018
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, ...
Patterns 2 (6), 2021
692021
A generative modeling approach to limited channel ECG classification
D Rajan, JJ Thiagarajan
2018 40th Annual International Conference of the IEEE Engineering in …, 2018
442018
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
292020
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
232020
Calibrating healthcare ai: Towards reliable and interpretable deep predictive models
JJ Thiagarajan, P Sattigeri, D Rajan, B Venkatesh
arXiv preprint arXiv:2004.14480, 2020
232020
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
232013
Training calibration-based counterfactual explainers for deep learning models in medical image analysis
JJ Thiagarajan, K Thopalli, D Rajan, P Turaga
Scientific reports 12 (1), 597, 2022
222022
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, 58-63, 2016
222016
Designing counterfactual generators using deep model inversion
J Thiagarajan, VS Narayanaswamy, D Rajan, J Liang, A Chaudhari, ...
Advances in Neural Information Processing Systems 34, 16873-16884, 2021
212021
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
202014
Fair selective classification via sufficiency
JK Lee, Y Bu, D Rajan, P Sattigeri, R Panda, S Das, GW Wornell
International conference on machine learning, 6076-6086, 2021
182021
Leveraging medical visual question answering with supporting facts
T Kornuta, D Rajan, C Shivade, A Asseman, AS Ozcan
arXiv preprint arXiv:1905.12008, 2019
182019
Understanding Behavior of Clinical Models under Domain Shifts
JJ Thiagarajan, D Rajan, P Sattigeri
arXiv preprint arXiv:1809.07806, 2018
18*2018
DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms
JJ Thiagarajan, D Rajan, S Katoch, A Spanias
Scientific reports 10 (1), 16428, 2020
172020
Efficient brownfield optimization of a reservoir in west Siberia
OS Ushmaev, VM Babin, NG Glavnov, RR Yaubatyrov, DE Ciaurri, ...
Petroleum Geoscience 25 (2), 207-218, 2019
152019
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
132020
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
132014
Self-training with improved regularization for sample-efficient chest x-ray classification
D Rajan, JJ Thiagarajan, A Karargyris, S Kashyap
Medical Imaging 2021: Computer-Aided Diagnosis 11597, 418-425, 2021
122021
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
92018
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