October 10, 2025Frontiers in MedicineOpen Access

Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review

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XLXu Li XHXu Hu HXHuiting Xu

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Overview

Systematic review evaluates mortality risk prediction models for sepsis-associated acute kidney injury, highlighting model validation and methodological rigor.

Key Points

Machine learning models provide reliable mortality predictions for patients with sepsis-associated acute kidney injury, but biases exist.
Nine studies were analyzed, with commonly used methods including extreme gradient boosting, showing high area under the curve values.
The comprehensive assessment of existing prediction models indicated the need for standardized processes in feature selection and validation.
Future research should prioritize interpretability alongside robust model construction to ensure successful healthcare integration.

Cite This Study

Li et al. (2025) studied this question.

synapsesocial.com/papers/68e861907ef2f04ca37e3e03 https://doi.org/10.3389/fmed.2025.1680180

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October 10, 2025Frontiers in MedicineOpen Access

Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review

View Full Paper

Ask AI

Bookmark

Authors

XLXu Li XHXu Hu HXHuiting Xu

Discussion

Member takes

Overview

Systematic review evaluates mortality risk prediction models for sepsis-associated acute kidney injury, highlighting model validation and methodological rigor.

Key Points

Machine learning models provide reliable mortality predictions for patients with sepsis-associated acute kidney injury, but biases exist.
Nine studies were analyzed, with commonly used methods including extreme gradient boosting, showing high area under the curve values.
The comprehensive assessment of existing prediction models indicated the need for standardized processes in feature selection and validation.
Future research should prioritize interpretability alongside robust model construction to ensure successful healthcare integration.

Cite This Study

Li et al. (2025) studied this question.

synapsesocial.com/papers/68e861907ef2f04ca37e3e03 https://doi.org/10.3389/fmed.2025.1680180

View Full Paper

Ask AI

Bookmark