Predicting Healthcare-associated Infections using Machine Learning: A Time-series Analysis Approach
Abstract
This paper presents a time-series analysis approach to predict healthcare-associated infections (HAIs) using machine learning techniques. By integrating data from electronic medical records, environmental sensors, and infection control protocols, the proposed AI model forecasts the likelihood of HAIs within healthcare facilities. The study evaluates the performance of various ML algorithms in detecting temporal patterns and early warning signs of infections, enabling proactive infection prevention strategies and enhancing patient safety in healthcare settings.
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