Web App for prediction of hospitalisation in Intensive Care Unit by covid-19

• Main Authors: Greici Capellari Fabrizzio (Author), Alacoque Lorenzini Erdmann (Author), Lincoln Moura de Oliveira (Author)
• Format: Book
• Published: Associação Brasileira de Enfermagem, 2023-12-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1984-0446; 10.1590/0034-7167-2022-0740
• Keywords: Inventions; Forecasting; Artificial Intelligence; Covid-19; Precision Medicine; Nursing; RT1-120
• Source: Revista Brasileira de Enfermagem, Vol 76, Iss 6 (2023)

ABSTRACT Objective: To develop a Web App from a predictive model to estimate the risk of Intensive Care Unit (ICU) admission for patients with covid-19. Methods: An applied technological production research was carried out with the development of Streamlit using Python, considering the decision tree model that presented the best performance (AUC 0.668). Results: Based on the variables associated with Precision Nursing, Streamlit stratifies patients admitted to clinical units who are most likely to be admitted to the Intensive Care Unit, serving as a decision-making support tool for healthcare professionals. Final considerations: The performance of the model may have been influenced by the start of vaccination during the data collection period, however, the Web App via Streamlit proved to be a feasible tool for presenting research results, due to the ease of understanding by nurses and its potential for supporting clinical decision-making.