| Literature DB >> 31438331 |
Alejandro Renato1, Hernan Berinsky1, Mariana Daus1, Miguel Fantin Dachery1, Oscar Jauregui1, Fernando Storani1, María Laura Gambarte1, Carlos Otero1, Daniel Luna1.
Abstract
Clinical documentation in healthcare institutions is one of the daily tasks that consumes most of the time for those involved. The adoption of mobile devices in medical practice increases efficiency among healthcare professionals. We describe the design and evaluation of an automatic speech recognition system that enables the transcription of audio to text of clinical notes in a mobile environment. Our system achieved 94.1% word accuracy when evaluated on pediatrics, internal medicine and surgery services.Entities:
Keywords: Electronic Health Records; Mobile Applications; Speech Recognition Software
Mesh:
Year: 2019 PMID: 31438331 DOI: 10.3233/SHTI190635
Source DB: PubMed Journal: Stud Health Technol Inform ISSN: 0926-9630