Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence
Abstract The relevance of the study is due to the growing number of diseases of the cerebrovascular system, in particular stroke, which is one of the leading causes of disability and mortality in the world. To improve stroke risk prediction models in terms of efficiency and interpretability, we prop...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
BMC
2025-02-01
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Series: | BMC Medical Informatics and Decision Making |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12911-025-02894-z |
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