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 | 515 | 2018 |
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 | 77 | 2021 |
A generative modeling approach to limited channel ECG classification D Rajan, JJ Thiagarajan 2018 40th Annual International Conference of the IEEE Engineering in …, 2018 | 44 | 2018 |
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 | 33 | 2020 |
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 | 30 | 2022 |
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 | 25 | 2021 |
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 | 24 | 2020 |
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 | 23 | 2013 |
Calibrating healthcare ai: Towards reliable and interpretable deep predictive models JJ Thiagarajan, P Sattigeri, D Rajan, B Venkatesh arXiv preprint arXiv:2004.14480, 2020 | 22 | 2020 |
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 | 22 | 2016 |
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 | 20 | 2021 |
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 | 19 | 2014 |
Leveraging medical visual question answering with supporting facts T Kornuta, D Rajan, C Shivade, A Asseman, AS Ozcan arXiv preprint arXiv:1905.12008, 2019 | 18 | 2019 |
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 | 17 | 2020 |
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 | 15 | 2019 |
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 | 14 | 2020 |
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 | 13 | 2021 |
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 | 13 | 2014 |
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 | 9 | 2018 |