TY - GEN
T1 - Bigtexts
T2 - 1st International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AgeingWell 2015
AU - Calderón, Wilson Alzate
AU - Quimbaya, Alexandra Pomares
AU - Gonzalez, Rafael A.
AU - Muñoz, Oscar Mauricio
PY - 2015
Y1 - 2015
N2 - In the healthcare domain the analysis of Electronic Medical Records (EMR) may be classified as a Big Data problem since it has the three fundamental characteristics: Volume, Variety and Speed. A major drawback is that most of the information contained in medical records is narrative text, where natural language processing and text mining are key technologies to enhance the utility of medical records for research, analysis and decision support. Among the tasks performed for natural language processing, the most critical, in terms of time consumption, are the pre-processing tasks that give some structure to the original non-structured text. Studying existing research on the use of Big Data techniques in the healthcare domain reveals few practical contributions, especially for EMR analysis. To fill this gap, this paper presents BigTexts, a framework that provides pre-built functionalities for the execution of pre-processing tasks over narrative texts contained in EMR using Big Data techniques. BigTexts enables faster results on EMR narrative text analysis improving decision making in healthcare.
AB - In the healthcare domain the analysis of Electronic Medical Records (EMR) may be classified as a Big Data problem since it has the three fundamental characteristics: Volume, Variety and Speed. A major drawback is that most of the information contained in medical records is narrative text, where natural language processing and text mining are key technologies to enhance the utility of medical records for research, analysis and decision support. Among the tasks performed for natural language processing, the most critical, in terms of time consumption, are the pre-processing tasks that give some structure to the original non-structured text. Studying existing research on the use of Big Data techniques in the healthcare domain reveals few practical contributions, especially for EMR analysis. To fill this gap, this paper presents BigTexts, a framework that provides pre-built functionalities for the execution of pre-processing tasks over narrative texts contained in EMR using Big Data techniques. BigTexts enables faster results on EMR narrative text analysis improving decision making in healthcare.
KW - Big Data
KW - Electronic Medical Record
KW - Framework
KW - Natural language processing
KW - Text mining
UR - http://www.scopus.com/inward/record.url?scp=84939504373&partnerID=8YFLogxK
U2 - 10.5220/0005434101290136
DO - 10.5220/0005434101290136
M3 - Conference contribution
AN - SCOPUS:84939504373
T3 - ICT4AgeingWell 2015 - Proceedings of the 1st International Conference on Information and Communication Technologies for Ageing Well and e-Health
SP - 129
EP - 136
BT - ICT4AgeingWell 2015 - Proceedings of the 1st International Conference on Information and Communication Technologies for Ageing Well and e-Health
A2 - Holzinger, Andreas
A2 - Rocker, Carsten
A2 - Fred, Ana
A2 - Helfert, Markus
A2 - O'Donoghue, John
A2 - Ziefle, Martina
PB - SciTePress
Y2 - 20 May 2015 through 22 May 2015
ER -