title: MedTxting: learning based and knowledge rich SMS-style medical text contraction.
abstract: In mobile health (M-health), Short Message Service (SMS) has shown to improve disease related self-management and health service outcomes, leading to enhanced patient care. However, the hard limit on character size for each message limits the full value of exploring SMS communication in health care practices. To overcome this problem and improve the efficiency of clinical workflow, we developed an innovative system, MedTxting (available at http://medtxting.askhermes.org), which is a learning-based but knowledge-rich system that compresses medical texts in a SMS style. Evaluations on clinical questions and discharge summary narratives show that MedTxting can effectively compress medical texts with reasonable readability and noticeable size reduction. Findings in this work reveal potentials of MedTxting to the clinical settings, allowing for real-time and cost-effective communication, such as patient condition reporting, medication consulting, physicians connecting to share expertise to improve point of care.
authors.affiliation: University of Wisconsin Milwaukee, Milwaukee, WI, USA.
authors.forename: Feifan
authors.initials: F
authors.lastname: Liu
authors.forename: Soheil
authors.initials: S
authors.lastname: Moosavinasab
authors.forename: Thomas K
authors.initials: TK
authors.lastname: Houston
authors.forename: Hong
authors.initials: H
authors.lastname: Yu
mesh_terms: D006801:Humans; D010865:Pilot Projects; D017216:Telemedicine / Q000379:methods*; D060145:Text Messaging