| The TUH EEG CORPUS: A big data resource for automated EEG interpretation A Harati, S Lopez, I Obeid, J Picone, MP Jacobson, S Tobochnik 2014 IEEE signal processing in medicine and biology symposium (SPMB), 1-5, 2014 | 131 | 2014 |
| Automatic analysis of EEGs using big data and hybrid deep learning architectures M Golmohammadi, AH Harati Nejad Torbati, S Lopez de Diego, I Obeid, ... Frontiers in human neuroscience 13, 76, 2019 | 111 | 2019 |
| Improved EEG event classification using differential energy A Harati, M Golmohammadi, S Lopez, I Obeid, J Picone 2015 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), 1-4, 2015 | 57 | 2015 |
| Systems and methods for mental health assessment EE Shriberg, M Aratow, M Islam, A Harati, T Rutowski, D Lin, Y Lu, ... US Patent App. 16/523,298, 2019 | 50 | 2019 |
| Detecting paroxysmal coughing from pertussis cases using voice recognition technology D Parker, J Picone, A Harati, S Lu, MH Jenkyns, PM Polgreen PloS one 8 (12), e82971, 2013 | 35 | 2013 |
| The temple university hospital eeg corpus A Harati, S Choi, M Tabrizi, I Obeid, J Picone, MP Jacobson 2013 IEEE Global Conference on Signal and Information Processing, 29-32, 2013 | 31 | 2013 |
| A doubly hierarchical Dirichlet process hidden Markov model with a non-ergodic structure AHHN Torbati, J Picone IEEE/ACM Transactions on Audio, Speech, and Language Processing 24 (1), 174-184, 2015 | 28 | 2015 |
| Speech-based depression prediction using encoder-weight-only transfer learning and a large corpus A Harati, E Shriberg, T Rutowski, P Chlebek, Y Lu, R Oliveira ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 25 | 2021 |
| Characterization of mammary tumors using noninvasive tactile and hyperspectral sensors A Sahu, F Saleheen, V Oleksyuk, C McGoverin, N Pleshko, AHHN Torbati, ... IEEE Sensors Journal 14 (10), 3337-3344, 2014 | 21 | 2014 |
| Systems and methods for mental health assessment EE Shriberg, M Aratow, M Islam, AHHN Torbati, T Rutowski, D Lin, Y Lu, ... US Patent App. 17/130,649, 2021 | 20 | 2021 |
| Speech acoustic unit segmentation using hierarchical dirichlet processes. AHHN Torbati, J Picone, M Sobel INTERSPEECH, 637-641, 2013 | 20 | 2013 |
| Systems and methods for mental health assessment EE Shriberg, M Aratow, M Islam, AHHN Torbati, T Rutowski, D Lin, Y Lu, ... US Patent 10,748,644, 2020 | 19 | 2020 |
| Optimizing Speech-Input Length for Speaker-Independent Depression Classification T Rutowski, A Harati, Y Lu, E Shriberg interspeech, 2019 | 18 | 2019 |
| Depression and anxiety prediction using deep language models and transfer learning T Rutowski, E Shriberg, A Harati, Y Lu, P Chlebek, R Oliveira 2020 7th International Conference on Behavioural and Social Computing (BESC …, 2020 | 15 | 2020 |
| Applications of Dirichlet process mixtures to speaker adaptation AHHN Torbati, J Picone, M Sobel 2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012 | 15 | 2012 |
| A left-to-right HDP-HMM with HDPM emissions AHHN Torbati, J Picone, M Sobel 2014 48th Annual Conference on Information Sciences and Systems (CISS), 1-6, 2014 | 11 | 2014 |
| A Nonparametric Bayesian Approach for Spoken Term detection by Example Query AH Harati Nejad Torbati, J Picone Interspeech 2016, 2016 | 10* | 2016 |
| Cross-demographic portability of deep NLP-based depression models T Rutowski, E Shriberg, A Harati, Y Lu, R Oliveira, P Chlebek 2021 IEEE spoken language technology workshop (SLT), 1052-1057, 2021 | 8 | 2021 |
| Feasibility of a machine learning-based smartphone application in detecting depression and anxiety in a generally senior population D Lin, T Nazreen, T Rutowski, Y Lu, A Harati, E Shriberg, P Chlebek, ... Frontiers in Psychology 13, 811517, 2022 | 7 | 2022 |
| Toward Corpus Size Requirements for Training and Evaluating Depression Risk Models Using Spoken Language. T Rutowski, A Harati, E Shriberg, Y Lu, P Chlebek, R Oliveira INTERSPEECH, 3343-3347, 2022 | 7 | 2022 |
