| Exploration of physiological sensors, features, and machine learning models for pain intensity estimation F Pouromran, S Radhakrishnan, S Kamarthi Plos one 16 (7), e0254108, 2021 | 65 | 2021 |
| Personalized Deep Bi-LSTM RNN based model for pain intensity classification using EDA signal F Pouromran, Y Lin, S Kamarthi Sensors 22 (21), 8087, 2022 | 22 | 2022 |
| Analysis of pain research literature through keyword co-occurrence networks B Ozek, Z Lu, F Pouromran, S Radhakrishnan, S Kamarthi PLOS Digital Health 2 (9), e0000331, 2023 | 8 | 2023 |
| Automatic pain recognition from Blood Volume Pulse (BVP) signal using machine learning techniques F Pouromran, Y Lin, S Kamarthi arXiv preprint arXiv:2303.10607, 2023 | 6 | 2023 |
| Review and analysis of pain research literature through keyword co-occurrence networks B Ozek, Z Lu, F Pouromran, S Kamarthi arXiv preprint arXiv:2211.04289, 2022 | 2 | 2022 |
| Machine Learning for Automated Pain Assessment Using Physiological Signals F Pouromran Northeastern University, 2022 | | 2022 |
| Customer Similarities and Helpful Online Reviews M Ahmadian, F Pouromran | | |
