2018 ACL ACL 2018

Toward Cross-Domain Engagement Analysis in Medical Notes

Abstract

AbstractWe present a novel annotation task evaluating a patient’s engagement with their health care regimen. The concept of engagement supplements the traditional concept of adherence with a focus on the patient’s affect, lifestyle choices, and health goal status. We describe an engagement annotation task across two patient note domains: traditional clinical notes and a novel domain, care manager notes, where we find engagement to be more common. The annotation task resulted in a kappa of .53, suggesting strong annotator intuitions regarding engagement-bearing language. In addition, we report the results of a series of preliminary engagement classification experiments using domain adaptation.

🌉 Interdisciplinary Bridge — Healthcare & Medicine and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — cross-domain analysis
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio