@inproceedings{7cf3696f3b1f41e0932fb6d9f0c5968b,
title = "Patient-like-mine: A real time, visual analytics tool for clinical decision support",
abstract = "We developed a real-time, visual analytics tool for clinical decision support. The system expands the «recall of past experience» approach that a provider (physician) uses to formulate a course of action for a given patient. By utilizing Big-Data techniques, we enable the provider to recall all similar patients from an institution's electronic medical record (EMR) repository, to explore «what-if» scenarios, and to collect these evidence-based cohorts for future statistical validation and pattern mining.",
keywords = "clinical decision support, data mining, electronic medical record, real-time analytics, visual analytics",
author = "Peter Li and Yates, {Simon N.} and Lovely, {Jenna K.} and Larson, {David W.}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 3rd IEEE International Conference on Big Data, IEEE Big Data 2015 ; Conference date: 29-10-2015 Through 01-11-2015",
year = "2015",
month = dec,
day = "22",
doi = "10.1109/BigData.2015.7364104",
language = "English (US)",
series = "Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2865--2867",
editor = "Feng Luo and Kemafor Ogan and Zaki, {Mohammed J.} and Laura Haas and Ooi, {Beng Chin} and Vipin Kumar and Sudarsan Rachuri and Saumyadipta Pyne and Howard Ho and Xiaohua Hu and Shipeng Yu and Hsiao, {Morris Hui-I} and Jian Li",
booktitle = "Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015",
}