Neural Prediction of Patient Needs in an Ovarian Cancer Online Discussion Forum

Abstract

Social media is an important source to learn the concerns and needs of patients and caregivers in home care settings. However, manually identifying their needs can be labor-intensive and time-consuming. In this paper, we address the problem of need detection, automatically identifying patient needs in text. We explore both neural and traditional machine learning approaches, and evaluate them on a newly annotated dataset in an ovarian cancer discussion forum. We discuss issues and challenges of this novel task.