ArticleMultivariate behavioral research
Combinatorial Optimization of Clustering Decisions: An Approach to Refine Psychiatric Diagnoses.
Article in Multivariate behavioral research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Comparing the use of supervised machine learning variable selection methods in the context of two-group classification in the psychological and health sciences.Frontiers in psychology · 2026Article
- Conceptualization of Alcohol Use Disorder (AUD): Can Theoretical or Data Driven Approaches Improve the Construct Validity of AUD?Research on child and adolescent psychopathology · 2022Article
- Using Complete Enumeration to Derive "One-Size-Fits-All" Versus "Subgroup-Specific" Diagnostic Rules for Substance Use Disorder.Assessment · 2020Article
- Toward more efficient diagnostic criteria sets and rules: The use of optimization approaches in addiction science.Addictive behaviors · 2019Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Using complete enumeration (e.g., generating all possible subsets of item combinations) to evaluate clustering problems has the benefit of locating globally optimal solutions automatically without the concern of sampling variability. The proposed method is meant to combine clustering variables in such a way as to create groups that are maximally different on a theoretically sound derivation variable(s). After the population of all unique sets is permuted, optimization on some predefined, user-specific function can occur. We apply this technique to optimizing the diagnosis of Alcohol Use Disorder. This is a unique application, from a clustering point of view, in that the decision rule for clustering observations into the "diagnosis" group relies on both the set of items being considered and a predefined threshold on the number of items required to be endorsed for the "diagnosis" to occur. In optimizing diagnostic rules, criteria set sizes can be reduced without a loss of significant information when compared to current and proposed, alternative, diagnostic schemes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.