AttributeRank: An Algorithm for Attribute Ranking in Clinical Variable Selection

IF 2.1 4区医学 Q3 HEALTH CARE SCIENCES & SERVICES

Journal of evaluation in clinical practice Pub Date : 2024-12-20 DOI:10.1111/jep.14257

Donald Douglas Atsa'am, Ruth Wario, Pakiso Khomokhoana

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Abstract

Background

Risk difference is a valuable measure of association in epidemiology and healthcare which has the potential to be used in medical and clinical variable selection.

Objective

In this study, an attribute ranking algorithm, called AttributeRank, was developed to facilitate variable selection from clinical data sets.

Methods

The algorithm computes the risk difference between a predictor and the response variable to determine the level of importance of a predictor. The performance of the algorithm was compared with some existing variable selection algorithms using five clinical data sets on neonatal birthweight, bacterial survival after treatment, myocardial infarction, breast cancer, and diabetes.

Results

The variable subsets selected by AttributeRank yielded the highest average classification accuracy across the data sets, compared to Fisher score, Pearson's correlation, variable importance function, and Chi-Square.

Conclusion

AttributeRank proved to be more valuable in attribute ranking of clinical data sets compared to the existing algorithms and should be implemented in a user-friendly application in future research.

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来源期刊

Journal of evaluation in clinical practice 医学-卫生保健

CiteScore

4.80

自引率

4.20%

发文量

143

审稿时长

3-8 weeks

期刊介绍： The Journal of Evaluation in Clinical Practice aims to promote the evaluation and development of clinical practice across medicine, nursing and the allied health professions. All aspects of health services research and public health policy analysis and debate are of interest to the Journal whether studied from a population-based or individual patient-centred perspective. Of particular interest to the Journal are submissions on all aspects of clinical effectiveness and efficiency including evidence-based medicine, clinical practice guidelines, clinical decision making, clinical services organisation, implementation and delivery, health economic evaluation, health process and outcome measurement and new or improved methods (conceptual and statistical) for systematic inquiry into clinical practice. Papers may take a classical quantitative or qualitative approach to investigation (or may utilise both techniques) or may take the form of learned essays, structured/systematic reviews and critiques.