• Dec 20, 2017 News!ACMLC 2017 has been successfully held in NEC, Singapore during December 8-10.   [Click]
  • Dec 12, 2017 News!Good News! All papers from Volume 7, Number 1 to Volume 7, Number 5 have been indexed by Scopus!   [Click]
  • Mar 05, 2018 News!Welcome Assoc. Prof. Xianghua Xie, University of Swansea, UK joins our editorial board.
Search
General Information
Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2013 Vol.3(5): 449-452 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.358

Drill-Locate-Drill Algorithm for Diagnostic Reasoning in Psychiatry

Irosh Fernando and Frans A. Henskens
Abstract—This paper introduces a top-down algorithm for diagnosing psychiatric illnesses. It is based on the conceptualisation of diagnostic categories, diagnosis, and symptoms as a hierarchical model. The algorithm assumes that there exist a few close-ended clinical questions that can be used during clinical interview to rule in and rule out diagnostic categories, diagnoses and their symptoms. Compared to a more exhaustive bottom-up and recursive algorithm, which the authors have previously introduced, this algorithm has the advantage of being easy to implement requiring a less extensive knowledgebase. It is expected the algorithm will be used as a useful screening tool that increases the detection of psychiatric disorders, which are common but unfortunately currently under-diagnosed.

Index Terms—Diagnosis, diagnostic algorithm, psychiatry, screening tool.

The authors are with the School of Electrical Engineering & Computer Science, University of Newcastle, NSW 2308, Australia (phone: +61 423 281 664; e-mail: irosh.fernando@uon.edu.au, frans.henskens@newcastle.edu.au).

[PDF]

Cite:Irosh Fernando and Frans A. Henskens, "Drill-Locate-Drill Algorithm for Diagnostic Reasoning in Psychiatry," International Journal of Machine Learning and Computing vol.3, no. 5, pp. 449-452, 2013.

Copyright © 2008-2018. International Journal of Machine Learning and Computing. All rights reserved.
E-mail: ijmlc@ejournal.net