Exploring the Advancements of AI Enabled Clinical Decision Support Systems for Patient Triage in Healthcare
As the demand for medical services grows, the need for an efficient care process becomes increasingly urgent. Recent events have highlighted that the demad for services exceeds the available supply. In response, the focus of heaht information technology has shifted toward advanced clinical decision support systems (CDSS) to addess the critical challenges facing the medical industry. However, many healthcare organiztions lack robust clinical systems and tools. This research presents a comprehensive study of current industry applications, its related works, and provides insights into optimizing current state of the art machine learning (ML) CDSS with newer technologies, such as generative artificial intelligence-based knowledge graphs. This paper offers an overview of CDSS, details the patient treatment process and triage methods, explores the capabilities of knowledge graphs in healthcare, and underscores the need to incorporate machine learning into these processes to increase intelligence, robustness, and personalization.
Authors
- Jose M. Ruiz Mejia (ORCID: https://orcid.org/0000-0002-6923-5612)
- Danda B. Rawat
Institutions
- Howard University (US)
Publication Details
- Published
- 2024-11-18
- DOI
- https://doi.org/10.1109/healthcom60970.2024.10880833
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 1.42
Funders
- Howard University