TY - GEN
T1 - Clinical informatics to diagnose cardiac diseases based on data mining
AU - Ha, Sung Ho
AU - Zhang, Zhen Yu
PY - 2010
Y1 - 2010
N2 - The Emergency Department (ED) has been frustrated by the problems of overcrowding, long waiting times, and high costs over decades. With the development of computer techniques, various kinds of information systems have appeared and made people work more effectively. The Emergency Department Information System (EDIS) has been heralded as a "must" for the modern ED, which can enhance patients care, decrease the waiting time and cost, and alleviate the problem of overcrowding. This paper targets at building an engine of use in an EDIS. Based on the frameworks of patients flow in ED, real-world data were collected from the electronic medical records at the Emergency Department: more than 210000 records of 842 registered chest pain patients in total. By utilizing the data mining techniques, an engine of an expert system was proposed to help physicians with faster and more accurate decision making of diagnosis and lab test selections.
AB - The Emergency Department (ED) has been frustrated by the problems of overcrowding, long waiting times, and high costs over decades. With the development of computer techniques, various kinds of information systems have appeared and made people work more effectively. The Emergency Department Information System (EDIS) has been heralded as a "must" for the modern ED, which can enhance patients care, decrease the waiting time and cost, and alleviate the problem of overcrowding. This paper targets at building an engine of use in an EDIS. Based on the frameworks of patients flow in ED, real-world data were collected from the electronic medical records at the Emergency Department: more than 210000 records of 842 registered chest pain patients in total. By utilizing the data mining techniques, an engine of an expert system was proposed to help physicians with faster and more accurate decision making of diagnosis and lab test selections.
KW - Apriori algorithm
KW - C5.0 algorithm
KW - Data mining
KW - Emergency department
KW - Expert system
UR - http://www.scopus.com/inward/record.url?scp=78049461031&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-15020-3_6
DO - 10.1007/978-3-642-15020-3_6
M3 - Conference contribution
AN - SCOPUS:78049461031
SN - 3642150195
SN - 9783642150197
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 67
EP - 77
BT - Information Technology in Bio- and Medical Informatics, ITBAM 2010 - First International Conference, Proceedings
T2 - 1st International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2010
Y2 - 1 September 2010 through 2 September 2010
ER -