| Attend and diagnose: Clinical time series analysis using attention models H Song, D Rajan, JJ Thiagarajan, A Spanias arXiv preprint arXiv:1711.03905, 2017 | 112 | 2017 |
| Assessing individual performance in Agile undergraduate software engineering teams RF Gamble, ML Hale 2013 IEEE Frontiers in Education Conference (FIE), 1678-1684, 2013 | 25 | 2013 |
| 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 | 19 | 2013 |
| A generative modeling approach to limited channel ECG classification D Rajan, JJ Thiagarajan 2018 40th Annual International Conference of the IEEE Engineering in …, 2018 | 14 | 2018 |
| 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 | 14 | 2014 |
| 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 | 10 | 2014 |
| 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 | 8 | 2016 |
| Leveraging medical visual question answering with supporting facts T Kornuta, D Rajan, C Shivade, A Asseman, AS Ozcan arXiv preprint arXiv:1905.12008, 2019 | 7 | 2019 |
| 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 | 5 | 2016 |
| 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 | 5 | 2012 |
| Understanding Behavior of Clinical Models under Domain Shifts JJ Thiagarajan, D Rajan, P Sattigeri arXiv preprint arXiv:1809.07806, 2018 | 4* | 2018 |
| 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 | 3 | 2018 |
| 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 | 3 | 2013 |
| 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 | 2 | 2020 |
| 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 | 2 | 2020 |
| Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models JJ Thiagarajan, P Sattigeri, D Rajan, B Venkatesh arXiv preprint arXiv:2004.14480, 2020 | 2 | 2020 |
| 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 | 1 | 2020 |
| 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 | 1 | 2020 |
| Interactive signal processing education applications for the android platform S Ranganath, JJ Thiagarajan, D Rajan, MK Banavar, A Spanias, J Fan, ... Computers in Education Journal 10 (2), 2019 | 1 | 2019 |
| Automatic discrepancy detection in medical data D Rajan, T Syeda-Mahmood US Patent App. 15/295,865, 2018 | 1 | 2018 |
Jayaraman J. ThiagarajanMachine Learning Researcher, Lawrence Livermore National LabsVerified email at asu.edu
