AI-Based Decision Support Systems in Emergency Medicine: Enhancing Triage and Diagnosis
Abstract
Emergency medicine requires rapid decision-making, often with limited information and under time constraints. This paper explores the role of AI-based decision support systems (DSS) in improving triage and diagnosis in emergency settings. By integrating patient data, clinical guidelines, and historical case studies, AI algorithms can assist emergency healthcare providers in prioritizing cases, diagnosing conditions, and recommending appropriate treatments. The paper discusses the use of machine learning techniques, such as decision trees and ensemble methods, in triage systems, as well as the challenges of ensuring system reliability, accuracy, and integration with existing emergency medical workflows.
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