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Clinical Timing-Sequence Warning Models for Serious Bacterial Infections in Adults Based on Machine Learning: Retrospective Study.

Jian LiuJia ChenYongquan DongYan LouYu TianHuiyao SunYuqing JinJing-Song LiYunqing Qiu
Published in: Journal of medical Internet research (2023)
The clinical timing-sequence warning models demonstrated efficacy in predicting SBIs in patients suspected of having infective fever and in clinical application, suggesting good potential in clinical decision-making. Nevertheless, additional prospective and multicenter studies are necessary to further confirm their clinical utility.
Keyphrases
  • machine learning
  • end stage renal disease
  • prognostic factors
  • pulmonary embolism
  • deep learning
  • human health