Title: A study on suicidal risks in psychiatric adults
Authors: Subhagata Chattopadhyay, Farhad Daneshgar
Addresses: Department of Computer Science and Engineering, National Institute of Science and Technology, School of Computing, Palur Hills, Berhampur 761008, Orissa, India. ' School of Information Systems, Technology and Management, Australian School of Business, The University of New South Wales, Sydney NSW 2052, Australia
Abstract: Psychiatric patients often commit suicide during illness. Although the occurrences of suicides could be prevented, yet detection of risks at the early stage of the illness is a difficult task as hardly any warning sign/symptom could be detected. This study addresses this important issue and proposes a methodology to: a) explore the hidden factors in a set of adult psychiatric patients with the help of Pierce|s Suicide Intent Scales (PSIS); b) clustering psychiatric illnesses based on the risk levels using Single Linkage Hierarchical Clustering Algorithm (SLHCA). It further argues that together these observations could be useful for early detection of suicidal risks.
Keywords: psychiatric illnesses; SISs; suicide intent scales; statistical data mining; SLHCA; single linkage hierarchical clustering algorithm; suicide risks; adult psychiatric patients; suicidal tendencies.
DOI: 10.1504/IJBET.2011.039928
International Journal of Biomedical Engineering and Technology, 2011 Vol.5 No.4, pp.390 - 408
Published online: 21 Jan 2015 *
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