Clinical Decision Support System (CDSS) for Demand Management in the Healthcare Supply: A Case Study of Impacts Status (Risks) During Pregnancy
Abstract
In recent years, the medical industry has showed interest in reorganizing its operations to accommodate technological advancements and incorporating decision support systems into normal clinical procedures. Clinical Decision Support Systems (CDSS) connect observations and knowledge of health in order to encourage physicians to make health-related decisions in order to improve health care. The goal of this study is to examine the problems with Clinical Decision Support Systems (CDSS) and to concentrate on their utility in improving clinical practice. This article contained a case study of CDSS implementation for High-Risk Pregnancy (HRPCDSS) and a description of the conditions for a successful CDSS implementation. We will provide a Clinical Decision Support System (HRPCDSS) that will aid doctors in estimating the probability of an illness, and this process enhances their ability to offer therapeutic advice. In this study that eliminates the risk factors that community midwife’s/lady health visitors encounter in providing standardized/effective healthcare services to mothers and children. In this study, we suggest using the C4.5 algorithm decision trees to identify these diseases and compare their effectiveness and correction rates.
Fields of Study & Subjects
Artificial Intelligence in Healthcare
Artificial Intelligence and Decision Support Systems
Cognitive Science and Mapping
Publication details
- Journal / source
- Journal of Kufa for Mathematics and Computer
- Volume
- 12
- Issue
- 1
- Pages
- 32–45
- Publication date
- 5 January 2026