A novel Network Science Algorithm for Improving Triage of Patients
Pietro Hiram Guzzi Annamaria De Filippo Pierangelo Veltri
Patient triage plays a crucial role in healthcare, ensuring timely and
appropriate care based on the urgency of patient conditions. Traditional triage
methods heavily rely on human judgment, which can be subjective and prone to
errors. Recently, a growing interest has been in leveraging artificial
intelligence (AI) to develop algorithms for triaging patients. This paper
presents the development of a novel algorithm for triaging patients. It is
based on the analysis of patient data to produce decisions regarding their
prioritization. The algorithm was trained on a comprehensive data set
containing relevant patient information, such as vital signs, symptoms, and
medical history. The algorithm was designed to accurately classify patients
into triage categories through rigorous preprocessing and feature engineering.
Experimental results demonstrate that our algorithm achieved high accuracy and
performance, outperforming traditional triage methods. By incorporating
computer science into the triage process, healthcare professionals can benefit
from improved efficiency, accuracy, and consistency, prioritizing patients
effectively and optimizing resource allocation. Although further research is
needed to address challenges such as biases in training data and model
interpretability, the development of AI-based algorithms for triaging patients
shows great promise in enhancing healthcare delivery and patient outcomes.