Classification and predictive models using supervised machine learning: A conceptual review

Supervised machine learning models (SMLMs) are likely to be a prevalent approach in the literature on medical machine learning. These models have considerable potential to improve clinical decision-making through enhanced prediction and classification. In this review, we present an overview of SMLMs...

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Bibliographic Details
Published in:The Southern African journal of critical care : the official journal of the Critical Care Society Vol. 41; no. 1; p. e2937
Main Authors: Pienaar, M A, Naidoo, K D
Format: Journal Article
Language:English
Published: South Africa 01.04.2025
Subjects:
Supervised machine learning models
prediction
model development
model explanation
classification
machine learning
SMLM
validation
ISSN:2078-676X, 2078-676X
Online Access:Get more information
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Summary:Supervised machine learning models (SMLMs) are likely to be a prevalent approach in the literature on medical machine learning. These models have considerable potential to improve clinical decision-making through enhanced prediction and classification. In this review, we present an overview of SMLMs. We provide a discussion of the conceptual domains relevant to machine learning, model development, validation, and model explanation. This discussion is accompanied by clinical examples to illustrate key concepts. This conceptual review provides an overview and guide to the interpretation of SMLMs in the medical literature.
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ISSN:2078-676X
2078-676X
DOI:10.7196/SAJCC.2025.v411.2937