4.5 Article

Design and Implementation of a Comprehensive AI Dashboard for Real-Time Prediction of Adverse Prognosis of ED Patients

期刊

HEALTHCARE
卷 10, 期 8, 页码 -

出版社

MDPI
DOI: 10.3390/healthcare10081498

关键词

artificial intelligence; machine learning; big data; emergency department; dashboard; prognosis; prediction model

资金

  1. Chi Mei Medical Center [CMFHR111128, CMFHR11182]

向作者/读者索取更多资源

This study developed an AI dashboard for emergency department (ED) to monitor the real-time risk of patients. The ED medical staff found the dashboard to be easy to use, useful, and acceptable.
The emergency department (ED) is at the forefront of medical care, and the medical team needs to make outright judgments and treatment decisions under time constraints. Thus, knowing how to make personalized and precise predictions is a very challenging task. With the advancement of artificial intelligence (AI) technology, Chi Mei Medical Center (CMMC) adopted AI, the Internet of Things (IoT), and interaction technologies to establish diverse prognosis prediction models for eight diseases based on the ED electronic medical records of three branch hospitals. CMMC integrated these predictive models to form a digital AI dashboard, showing the risk status of all ED patients diagnosed with any of these eight diseases. This study first explored the methodology of CMMC's AI development and proposed a four-tier AI dashboard architecture for ED implementation. The AI dashboard's ease of use, usefulness, and acceptance was also strongly affirmed by the ED medical staff. The ED AI dashboard is an effective tool in the implementation of real-time risk monitoring of patients in the ED and could improve the quality of care as a part of best practice. Based on the results of this study, it is suggested that healthcare institutions thoughtfully consider tailoring their ED dashboard designs to adapt to their unique workflows and environments.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据