Emergency department use and Artificial Intelligence in Pelotas: design and baseline results.

Felipe Mendes Delpino Lílian Munhoz Figueiredo Ândria Krolow Costa Ioná Carreno Luan Nascimento da Silva Alana Duarte Flores Milena Afonso Pinheiro Eloisa Porciúncula da Silva Gabriela Ávila Marques Mirelle de Oliveira Saes Suele Manjourany Silva Duro Luiz Augusto Facchini João Ricardo Nickening Vissoci Thaynã Ramos Flores Flavio Fernando Demarco Cauane Blumenberg Alexandre Dias Porto Chiavegatto Filho Inácio Crochemore Mohnsam da Silva Sandro Rogério Rodrigues Batista Ricardo Alexandre Arcêncio Bruno Pereira Nunes

Published in: Revista brasileira de epidemiologia = Brazilian journal of epidemiology (2023)

The present paper presented a protocol describing the steps that were and will be taken to produce a model capable of predicting the demand for urgent and emergency services in one year among residents of Pelotas, in Rio Grande do Sul state.

Keyphrases

artificial intelligence
emergency department
machine learning
big data
deep learning
healthcare
randomized controlled trial
primary care
mental health
public health