no code implementations • 14 Nov 2023 • Burcu Ozek, Zhenyuan Lu, Srinivasan Radhakrishnan, Sagar Kamarthi
As LossS outperforms, we assessed its performance in three different scenarios for pain assessment: (1) a generalized approach (single model for the entire population), (2) a personalized approach (separate model for each individual), and (3) a hybrid approach (separate model for each cluster of individuals).
no code implementations • 19 Mar 2023 • Fatemeh Pouromran, Yingzi Lin, Sagar Kamarthi
In this study, we applied machine learning techniques on BVP signals to device a non-invasive modality for pain sensing.
1 code implementation • 13 Mar 2023 • Zhenyuan Lu, Burcu Ozek, Sagar Kamarthi
These results confirm that our approach can be utilized for automated classification of pain intensity using physiological signals to improve pain management and treatment.
no code implementations • 8 Nov 2022 • Burcu Ozek, Zhenyuan Lu, Fatemeh Pouromran, Sagar Kamarthi
Pain is a significant public health problem as the number of individuals with a history of pain globally keeps growing.
no code implementations • 28 Jun 2019 • Ramin Mohammadi, Sarthak Jain, Stephen Agboola, Ramya Palacholla, Sagar Kamarthi, Byron C. Wallace
We develop machine learning models (logistic regression and recurrent neural networks) to stratify patients with respect to the risk of exhibiting uncontrolled hypertension within the coming three-month period.