TY - JOUR
T1 - An Apriori Algorithm-Based Association Rule Analysis to detect Human Suicidal Behaviour
AU - Hassan, Md Mehedi
AU - Karim, Asif
AU - Mollick, Swarnali
AU - Azam, Sami
AU - Ignatious, Eva
AU - Farhan Al Haque, A. S.M.
N1 - Publisher Copyright:
© 2023 Elsevier B.V.. All rights reserved.
PY - 2023
Y1 - 2023
N2 - Suicide is a major cause of death. It is also a complex public health issue and often preventable with timely intervention. Overall, the rate of suicide is increasing for various reasons. In our study, we use an association rule analysis to find the most important rules to predict suicidal behavior from an available data set. One of the most powerful machine learning algorithms available for identifying associations within databases is the Apriori algorithm. We used this algorithm to analyze association rules of suicidal behavior using a dataset of 1250 instances and 27 impactful features. These include daily activities, family background, and answers to mental questionnaires and have been analyzed to find combinations that are associated with suicidal behavior. The study has resulted in some key rules for human suicidal behavior. The Apriori method has been used to identify the eight most significant rules with the support of 0.25 and the confidence of 0.90.
AB - Suicide is a major cause of death. It is also a complex public health issue and often preventable with timely intervention. Overall, the rate of suicide is increasing for various reasons. In our study, we use an association rule analysis to find the most important rules to predict suicidal behavior from an available data set. One of the most powerful machine learning algorithms available for identifying associations within databases is the Apriori algorithm. We used this algorithm to analyze association rules of suicidal behavior using a dataset of 1250 instances and 27 impactful features. These include daily activities, family background, and answers to mental questionnaires and have been analyzed to find combinations that are associated with suicidal behavior. The study has resulted in some key rules for human suicidal behavior. The Apriori method has been used to identify the eight most significant rules with the support of 0.25 and the confidence of 0.90.
KW - Apriori
KW - Association Rule Mining
KW - Behaviour Analysis
KW - Suicidal Behaviour
KW - Suicide
UR - http://www.scopus.com/inward/record.url?scp=85161742377&partnerID=8YFLogxK
U2 - 10.1016/j.procs.2023.01.412
DO - 10.1016/j.procs.2023.01.412
M3 - Conference article
AN - SCOPUS:85161742377
SN - 1877-0509
VL - 219
SP - 1279
EP - 1288
JO - Procedia Computer Science
JF - Procedia Computer Science
T2 - 2022 International Conference on ENTERprise Information Systems, CENTERIS 2022 - International Conference on Project MANagement, ProjMAN 2022 and International Conference on Health and Social Care Information Systems and Technologies, HCist 2022
Y2 - 9 November 2022 through 11 November 2022
ER -