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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| Vydáno v: | The Southern African journal of critical care : the official journal of the Critical Care Society Ročník 41; číslo 1; s. e2937 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
South Africa
01.04.2025
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| Témata: | |
| ISSN: | 2078-676X, 2078-676X |
| On-line přístup: | Zjistit podrobnosti o přístupu |
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| Shrnutí: | 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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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 2078-676X 2078-676X |
| DOI: | 10.7196/SAJCC.2025.v411.2937 |