Prioritizing Hospital Admission According to Emergency Using Machine Learning

Abstract: The use of artificial intelligence and machine learning techniques in emergency medicine has grown rapidly. This paper reviews and assesses studies in this field, categorizing them into three areas: prediction and detection of disease, prediction of need for admission, discharge, and mortality, and machine learning-based triage systems. Overall, the studies reviewed demonstrate the potential of artificial intelligence in improving emergency care. However, the accuracy and effectiveness of these algorithms depend on data quality. Further research is needed to validate findings and improve performance in clinical settings.

Machine Learning, Logistic Regression, Naive Bayes, Random Forest, LSTM, Emergency Medicine

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