@inproceedings{344ba8b2179e431eba2b44a49069aa68,
title = "Rosacea patients are at higher risk for obstructive sleep apnea: Automated retrospective research",
abstract = "Using big data science we employ NLP and a novel interface the BMI Investigator to answer clinically meaninful questions. The use case presented is the association between Rosacea and Obstructive Sleep Apnea.",
keywords = "Big data science, Information Retreival, NLP, Obstructive Sleep Apnea, Rosacea",
author = "Elkin, \{Peter L.\} and Sarah Mullin and Sylvester Sakilay",
note = "Publisher Copyright: {\textcopyright} 2020 European Federation for Medical Informatics (EFMI) and IOS Press.; 30th Medical Informatics Europe Conference, MIE 2020 ; Conference date: 28-04-2020 Through 01-05-2020",
year = "2020",
month = jun,
day = "16",
doi = "10.3233/SHTI200452",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press",
pages = "1381--1382",
editor = "Pape-Haugaard, \{Louise B.\} and Christian Lovis and Madsen, \{Inge Cort\} and Patrick Weber and Nielsen, \{Per Hostrup\} and Philip Scott",
booktitle = "Digital Personalized Health and Medicine - Proceedings of MIE 2020",
}