Fusing audio, visual and textual clues for sentiment analysis from multimodal content S Poria, E Cambria, N Howard, GB Huang, A Hussain Neurocomputing 174, 50-59, 2016 | 605 | 2016 |
The use of photoplethysmography for assessing hypertension M Elgendi, R Fletcher, Y Liang, N Howard, NH Lovell, D Abbott, K Lim, ... NPJ digital medicine 2 (1), 60, 2019 | 517 | 2019 |
Comparing oversampling techniques to handle the class imbalance problem: A customer churn prediction case study A Amin, S Anwar, A Adnan, M Nawaz, N Howard, J Qadir, A Hawalah, ... Ieee Access 4, 7940-7957, 2016 | 337 | 2016 |
Enhanced SenticNet with affective labels for concept-based opinion mining S Poria, A Gelbukh, A Hussain, N Howard, D Das, S Bandyopadhyay IEEE Intelligent Systems 28 (2), 31-38, 2013 | 273 | 2013 |
Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis S Poria, H Peng, A Hussain, N Howard, E Cambria Neurocomputing 261, 217-230, 2017 | 235 | 2017 |
Metaphor identification in large texts corpora Y Neuman, D Assaf, Y Cohen, M Last, S Argamon, N Howard, O Frieder PloS one 8 (4), e62343, 2013 | 173 | 2013 |
Semantic multidimensional scaling for open-domain sentiment analysis E Cambria, Y Song, H Wang, N Howard IEEE intelligent systems 29 (2), 44-51, 2012 | 148 | 2012 |
Common sense knowledge based personality recognition from text S Poria, A Gelbukh, B Agarwal, E Cambria, N Howard Advances in Soft Computing and Its Applications: 12th Mexican International …, 2013 | 138 | 2013 |
Cuffless single-site photoplethysmography for blood pressure monitoring M Hosanee, G Chan, K Welykholowa, R Cooper, PA Kyriacou, D Zheng, ... Journal of clinical medicine 9 (3), 723, 2020 | 137 | 2020 |
Can photoplethysmography replace arterial blood pressure in the assessment of blood pressure? G Martínez, N Howard, D Abbott, K Lim, R Ward, M Elgendi Journal of clinical medicine 7 (10), 316, 2018 | 132 | 2018 |
Intention awareness: improving upon situation awareness in human-centric environments N Howard, E Cambria Human-centric Computing and Information Sciences 3, 1-17, 2013 | 127 | 2013 |
Subliminal priming—state of the art and future perspectives M Elgendi, P Kumar, S Barbic, N Howard, D Abbott, A Cichocki Behavioral Sciences 8 (6), 54, 2018 | 126 | 2018 |
Sentic blending: Scalable multimodal fusion for the continuous interpretation of semantics and sentics E Cambria, N Howard, J Hsu, A Hussain 2013 IEEE symposium on computational intelligence for human-like …, 2013 | 118 | 2013 |
The effectiveness of image augmentation in deep learning networks for detecting COVID-19: A geometric transformation perspective M Elgendi, MU Nasir, Q Tang, D Smith, JP Grenier, C Batte, B Spieler, ... Frontiers in Medicine 8, 629134, 2021 | 110 | 2021 |
Cognitive intelligence: Deep learning, thinking, and reasoning by brain-inspired systems Y Wang, B Widrow, LA Zadeh, N Howard, S Wood, VC Bhavsar, G Budin, ... International Journal of Cognitive Informatics and Natural Intelligence …, 2016 | 101 | 2016 |
How effective is pulse arrival time for evaluating blood pressure? Challenges and recommendations from a study using the MIMIC database Y Liang, D Abbott, N Howard, K Lim, R Ward, M Elgendi Journal of clinical medicine 8 (3), 337, 2019 | 99 | 2019 |
Automatic detection of acromegaly from facial photographs using machine learning methods X Kong, S Gong, L Su, N Howard, Y Kong EBioMedicine 27, 94-102, 2018 | 98 | 2018 |
Dependency-based semantic parsing for concept-level text analysis S Poria, B Agarwal, A Gelbukh, A Hussain, N Howard Computational Linguistics and Intelligent Text Processing: 15th …, 2014 | 85 | 2014 |
Detection of disease conditions and comorbidities N Howard US Patent 10,799,186, 2020 | 73 | 2020 |
Automatic identification of conceptual metaphors with limited knowledge L Gandy, N Allan, M Atallah, O Frieder, N Howard, S Kanareykin, ... Proceedings of the AAAI Conference on Artificial Intelligence 27 (1), 328-334, 2013 | 67 | 2013 |