Houssem Ben Khalfallah, M. Jelassi, J. Demongeot, Narjès Bellamine Ben Saoud
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引用次数: 2
Abstract
Objective
The objective of this study was to provide an overview of Decision Support Systems (DSS) applied in healthcare used for diagnosis, monitoring, prediction and recommendation in medicine.
Methods
We conducted a systematic review using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines of articles published until September 2022 from PubMed, Cochrane, Scopus and web of science databases. We used KH coder to analyze included research. Then we categorized decision support systems based on their types and medical applications.
Results
The search strategy provided a total of 1605 articles in the studied period. Of these, 231 articles were included in this qualitative review. This research was classified into 4 categories based on the DSS type used in healthcare: Alert Systems, Monitoring Systems, Recommendation Systems and Prediction Systems. Under each category, domain applications were specified according to the disease the system was applied to.
Conclusion
In this systematic review, we collected CDSS studies that use ML techniques to provide insights into different CDSS types. We highlighted the importance of ML to support physicians in clinical decision-making and improving healthcare according to their purposes.
本研究的目的是概述决策支持系统(DSS)在医疗保健中的应用,用于医学诊断、监测、预测和推荐。方法采用PRISMA (Preferred Reporting Items for systematic Reviews and Meta-Analysis)指南,对PubMed、Cochrane、Scopus和web of science数据库中截至2022年9月发表的文章进行了系统评价。我们使用KH编码器来分析纳入的研究。然后,我们根据决策支持系统的类型和医疗应用对其进行分类。结果本研究期间共检索到文献1605篇。其中,231篇文章被纳入本定性综述。本研究根据医疗保健中使用的DSS类型分为4类:警报系统、监测系统、推荐系统和预测系统。在每个类别下,根据系统应用的疾病指定域应用程序。在这篇系统综述中,我们收集了使用ML技术的CDSS研究,以提供对不同类型CDSS的见解。我们强调了ML在支持医生临床决策和根据其目的改善医疗保健方面的重要性。