| Spatio-temporal progression of cortical activity related to continuous overt and covert speech production in a reading task JS Brumberg, DJ Krusienski, S Chakrabarti, A Gunduz, P Brunner, ... PloS one 11 (11), e0166872, 2016 | 83 | 2016 |
| Progress in speech decoding from the electrocorticogram S Chakrabarti, HM Sandberg, JS Brumberg, DJ Krusienski Biomedical Engineering Letters 5, 10-21, 2015 | 73 | 2015 |
| GIST 2.0: A scalable multi-trait metric for quantifying population representativeness of individual clinical studies A Sen, S Chakrabarti, A Goldstein, S Wang, PB Ryan, C Weng Journal of biomedical informatics 63, 325-336, 2016 | 26 | 2016 |
| Correlating eligibility criteria generalizability and adverse events using Big Data for patients and clinical trials A Sen, PB Ryan, A Goldstein, S Chakrabarti, S Wang, E Koski, C Weng Annals of the New York Academy of Sciences 1387 (1), 34-43, 2017 | 25 | 2017 |
| The representativeness of eligible patients in type 2 diabetes trials: a case study using GIST 2.0 A Sen, A Goldstein, S Chakrabarti, N Shang, T Kang, A Yaman, PB Ryan, ... Journal of the American Medical Informatics Association 25 (3), 239-247, 2018 | 20 | 2018 |
| LORE: a large-scale offer recommendation engine with eligibility and capacity constraints R Makhijani, S Chakrabarti, D Struble, Y Liu Proceedings of the 13th ACM Conference on Recommender Systems, 160-168, 2019 | 17 | 2019 |
| An Interoperable Similarity-based Cohort Identification Method Using the OMOP Common Data Model Version 5.0 S Chakrabarti, A Sen, V Huser, GW Hruby, A Rusanov, ... Journal of Healthcare Informatics Research 2017, 1-18, 2017 | 12 | 2017 |
| Neural insights for digital marketing content design F Kong, Y Li, H Nassif, T Fiez, R Henao, S Chakrabarti Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 9 | 2023 |
| Predicting mel-frequency cepstral coefficients from electrocorticographic signals during continuous speech production S Chakrabarti, DJ Krusienski, G Schalk, JS Brumberg Proceedings of the Sixth International Neural Engineering Conference, 2013 | 6 | 2013 |
| How Have Cancer Clinical Trial Eligibility Criteria Evolved Over Time? A Yaman, S Chakrabarti, A Sen, C Weng Proceedings of AMIA Joint Summits, 2016 | 3 | 2016 |
| Assessing eligibility criteria generalizability and their correlations with adverse events using big data for EHRS and clinical trials A Sen, P Ryan, A Goldstein, S Chakrabarti, S Wang, C Weng Proceedings of the Data Science Learning and Applications to Biomedical and …, 2016 | 2 | 2016 |
| Characterization and Decoding of Speech Representations From the Electrocorticogram S Chakrabarti | 1 | 2015 |
| Progressive horizon learning: Adaptive long term optimization for personalized recommendation C Yi, D Zumwalt, Z Ni, S Chakrabarti Proceedings of the 17th ACM Conference on Recommender Systems, 940-946, 2023 | | 2023 |
| Method, system, and manufacture for min-cost flow item recommendations D Struble, R Makhijani, Y Liu, S Chakrabarti US Patent 11,367,118, 2022 | | 2022 |
| LORE: A large-scale offer recommendation engine through the lens of an online subscription service R Makhijani, S Chakrabarti, D Struble, Y Liu | | 2019 |
| Using ECoG Gamma Activity to Model the Mel-Frequency Cepstral Coefficients of Speech DJK S. Chakrabarti, J.S. Brumberg, A. Gunduz, P. Brunner, G. Schalk Proceedings of the Fifth International Brain-Computer Interface Meeting, 2013 | | 2013 |
| CMOS Implementation of the resistive network model of the outer plexiform layer of the retina. S Chakrabarti, A Sahu Proceedings of the Internal Conference on Scientific Paradigm Shift in …, 2011 | | 2011 |
Anando SenData Scientist, Newcastle University在 newcastle.ac.uk 的电子邮件经过验证
