Building gender-specific sexually transmitted infection risk prediction models using CatBoost algorithm and NHANES data

Building gender-specific sexually transmitted infection risk prediction models using CatBoost algorithm and NHANES data

Abstract Background and aims Sexually transmitted infections (STIs) are a significant global public health challenge due to their high incidence rate and potential for severe consequences when early intervention is neglected. Research shows an upward trend in absolute cases and DALY numbers of STIs,...

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Bibliographic Details
Main Authors: Mengjie Hu, Han Peng, Xuan Zhang, Lefeng Wang, Jingjing Ren
Format: Article
Language:English
Published: BMC 2024-01-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Sexually transmitted infections
CatBoost algorithm
NHANES data
SHAP algorithm
Online Access:https://doi.org/10.1186/s12911-024-02426-1

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