Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
April 11, 2024PLoS ONEOpen Access

Machine learning for prediction of acute kidney injury in patients diagnosed with sepsis in critical care

View Full Paper
Ask AI
Bookmark
Share

Authors

JSJianshan ShiHHHuirui HanSCSong Chen

Discussion

Loading...

Member takes

Overview

Key Points

Key points are not available for this paper at this time.

Cite This Study

Shi et al. (2024) studied this question.

synapsesocial.com/papers/68e6f83cb6db6435876722d2https://doi.org/10.1371/journal.pone.0301014
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Stage prediction of acute kidney injury in sepsis patients using explainable machine learning approaches2025
  2. 2Risk prediction of sepsis-associated acute kidney injury: development, validation of a machine learning model with multicenter data2026
  3. 3Machine learning model for predicting the risk of AKI in early hemodynamically stable sepsis patients: a study based on the MIMIC IV database2026
  4. 4An interpretable machine-learning model for predicting in-hospital mortality in patients with sepsis-associated acute kidney injury2026 · 1 citations
  5. 5Development of interpretable machine learning models for early diagnosis of sepsis-associated acute kidney injury2026