Pain Management

Pain management research is intensely focused on developing more accurate and personalized approaches to pain assessment and treatment. Current efforts leverage machine learning, employing neural networks (including MLPs and Transformers) and reinforcement learning algorithms to analyze diverse data sources, such as facial expressions, physiological signals (e.g., EDA), and patient-reported outcomes, to create objective pain intensity estimations and predict opioid use risk. This work emphasizes improving model interpretability and addressing potential biases, particularly concerning gender fairness, to ensure equitable and effective pain care. Ultimately, these advancements aim to optimize pain management strategies, reducing suffering and improving patient outcomes.

Papers

July 29, 2024

Synthetic Thermal and RGB Videos for Automatic Pain Assessment utilizing a Vision-MLP Architecture
Stefanos Gkikas, Manolis Tsiknakis
Thermal Image Single RGB Image Thermal Management MLP Architecture Pain Assessment Pain Management

February 29, 2024

Investigating Gender Fairness in Machine Learning-driven Personalized Care for Chronic Pain
Pratik Gajane, Sean Newman, Mykola Pechenizkiy, John D. Piette
Evidence Based Clinical Outcome Chronic Pain Gender Fairness Pain Management

November 14, 2023

Uncertainty Quantification in Neural-Network Based Pain Intensity Estimation
Burcu Ozek, Zhenyuan Lu, Srinivasan Radhakrishnan, Sagar Kamarthi
Uncertainty Quantification Pain Intensity Pain Assessment Pain Management

August 2, 2023

Enhancing Machine Learning Performance with Continuous In-Session Ground Truth Scores: Pilot Study on Objective Skeletal Muscle Pain Intensity Prediction
Boluwatife E. Faremi, Jonathon Stavres, Nuno Oliveira, Zhaoxian Zhou, Andrew H. Sung
Ground Truth Pilot Study Pain Intensity Pain Management

May 7, 2022

Individualized Risk Assessment of Preoperative Opioid Use by Interpretable Neural Network Regression
Yuming Sun, Jian Kang, Chad Brummett, Yi Li
Risk Score Opioid Use Pain Management

Pain Management

Papers

Synthetic Thermal and RGB Videos for Automatic Pain Assessment utilizing a Vision-MLP Architecture

Investigating Gender Fairness in Machine Learning-driven Personalized Care for Chronic Pain

Uncertainty Quantification in Neural-Network Based Pain Intensity Estimation

Enhancing Machine Learning Performance with Continuous In-Session Ground Truth Scores: Pilot Study on Objective Skeletal Muscle Pain Intensity Prediction

Individualized Risk Assessment of Preoperative Opioid Use by Interpretable Neural Network Regression