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Updated: Jun 25, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

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走向瘤学中的主动息护理:开发一种可解释的基于电子健康记录的机器学习模型,用于死亡风险预测

Qingyuan Zhuang1,2, Alwin Yaoxian Zhang3, Ryan Shea Tan Ying Cong4,5

  • 1Division of Supportive and Palliative Care, National Cancer Centre Singapore, 30 Hospital Blvd, Singapore, 168583, Singapore. zhuang.qingyuan@singhealth.com.sg.

BMC palliative care
|May 20, 2024
PubMed
概括

这项研究开发了一种可解释的机器学习模型,使用电子健康记录来预测晚期癌症患者的365天死亡风险,促进主动息护理. 该模型在识别需要支持性护理的患者方面表现强.

关键词:
临床决策支持系统临床决策支持系统电子健康记录电子健康记录机器学习是机器学习.在瘤学瘤学.抚慰性医学是一种缓解性医学.

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