TY - GEN
T1 - Heart disease diagnosis system with k-nearest neighbors method using real clinical medical records
AU - Enriko, I. Ketut Agung
AU - Suryanegara, Muhammad
AU - Gunawan, Dadang
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/6/25
Y1 - 2018/6/25
N2 - Heart disease is a serious disease that can lead to the death of a patient. Many types of research have been performed related to heart disease, including computer science-based research. Heart disease diagnosis studies, which aim to predict the type of heart disease from which a patient suffers, are popular and refer to some clinical parameters taken from the patient in the hospital. These data are then computed using data mining or machine learning techniques. Some algorithms can be utilized for this purpose, for example, Naïve Bayes, Support Vector Machine, and k-Nearest Neighbor algorithms. This research intends to diagnose heart disease using a sample of patient data. The data were collected from Harapan Kita Hospital, the biggest cardiovascular hospital in Indonesia. The patient clinical parameters selected are taken from complete data available in the hospital's medical records. The k-Nearest Neighbor method gave good results for heart disease diagnosis, and these results can be further used for another purpose, such as telemedicine or a machine-to-machine (M2M) based healthcare system.
AB - Heart disease is a serious disease that can lead to the death of a patient. Many types of research have been performed related to heart disease, including computer science-based research. Heart disease diagnosis studies, which aim to predict the type of heart disease from which a patient suffers, are popular and refer to some clinical parameters taken from the patient in the hospital. These data are then computed using data mining or machine learning techniques. Some algorithms can be utilized for this purpose, for example, Naïve Bayes, Support Vector Machine, and k-Nearest Neighbor algorithms. This research intends to diagnose heart disease using a sample of patient data. The data were collected from Harapan Kita Hospital, the biggest cardiovascular hospital in Indonesia. The patient clinical parameters selected are taken from complete data available in the hospital's medical records. The k-Nearest Neighbor method gave good results for heart disease diagnosis, and these results can be further used for another purpose, such as telemedicine or a machine-to-machine (M2M) based healthcare system.
KW - Data mining
KW - K-Nearest Neighbor
KW - Machine learning
KW - Machine learning algorithms
UR - http://www.scopus.com/inward/record.url?scp=85054805980&partnerID=8YFLogxK
U2 - 10.1145/3233347.3233386
DO - 10.1145/3233347.3233386
M3 - Conference contribution
AN - SCOPUS:85054805980
SN - 9781450364720
T3 - ACM International Conference Proceeding Series
SP - 127
EP - 131
BT - Proceedings of 2018 the 4th International Conference on Frontiers of Educational Technologies, ICFET 2018 - Workshop 2018 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018
PB - Association for Computing Machinery
T2 - 4th International Conference on Frontiers of Educational Technologies, ICFET 2018, Jointly with its Workshop the 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018
Y2 - 25 June 2018 through 27 June 2018
ER -