ConVIScope: Visual Analytics for Exploring Patient Conversations
This work addresses the problem of efficiently exploring patient conversations for healthcare professionals, but it is incremental as it builds on existing visual analytics and NLP techniques.
The authors tackled the challenge of analyzing large volumes of patient-doctor text conversations in mobile health by developing ConVIScope, a visual analytics system that integrates interactive visualization with natural language processing, with case studies involving six domain experts indicating its potential utility.
The proliferation of text messaging for mobile health is generating a large amount of patient-doctor conversations that can be extremely valuable to health care professionals. We present ConVIScope, a visual text analytic system that tightly integrates interactive visualization with natural language processing in analyzing patient-doctor conversations. ConVIScope was developed in collaboration with healthcare professionals following a user-centered iterative design. Case studies with six domain experts suggest the potential utility of ConVIScope and reveal lessons for further developments.