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.
History
Journal title
International Journal of Machine Learning and Computing
Volume
3
Issue
5
Pagination
449-452
Publisher
International Association of Computer Science and Information Technology Press (IACSIT Press)
Language
en, English
College/Research Centre
Faculty of Engineering and Built Environment
School
School of Electrical Engineering and Computer Science
Rights statement
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license