Combining machine learning models and rule engines in clinical decision systems: Exploring optimal aggregation methods for vaccine hesitancy prediction

Implementing such an aggregation method preserves the accuracy and capture rates of a clinical decision system, while potentially improving acceptance among healthcare providers.

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Publication Details

Journal
Computers in Biology and Medicine
Published
2025-02-20
DOI
https://doi.org/10.1016/j.compbiomed.2025.109749
Citations
5
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
12.40
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article

Combining machine learning models and rule engines in clinical decision systems: Exploring optimal aggregation methods for vaccine hesitancy prediction

J. Kucharski, Slawomir Kierner, Piotr Kierner
5 citations
Computers in Biology and Medicine
Machine Learning in Healthcare
12.40
article

Combining machine learning models and rule engines in clinical decision systems: Exploring optimal aggregation methods for vaccine hesitancy prediction

J. Kucharski, Slawomir Kierner, Piotr Kierner
article en
5 citations

Abstract

Implementing such an aggregation method preserves the accuracy and capture rates of a clinical decision system, while potentially improving acceptance among healthcare providers.

Computers in Biology and MedicineVol. 188
Lodz University of Technology (PL), Sinclair Community College (US), Massachusetts Institute of Technology (US)
Openalex Percentile: Top 2%
Machine Learning in Healthcare
12.40
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