Professor participates in AI study to predict risk of death in surgeries.

Project helps identify risk level in people with congenital heart disease undergoing surgery.

Professor João Chang Junior, PhD, a faculty member at ESEG, was one of the researchers who developed the study on predicting the risk of death in congenital heart disease patients undergoing surgery. The research resulted in a scientific article published in PLOS ONE, an internationally renowned journal, entitled: “Improving preoperative risk-of-death prediction in surgery congenital heart defects using an artificial intelligence model: a pilot study”.

“Reference Model for Improving Clinical and Surgical Processes in Patients with Heart Disease: management, optimization, and technical aspects” is a research project developed by 16 researchers – including a professor from ESEG – supervised by Professor Dr. Marcelo Biscegli Jatene, director of the Cardiac Surgery Unit at the Heart Institute of the Hospital das Clínicas of the Faculty of Medicine of USP (InCor-HCFMUSP). “The overall objective of the project is to develop a reference model to increase the efficiency and effectiveness of operational and managerial processes. It aims to provide more care to patients with congenital heart disease, with lower costs, less risk for these individuals, and the same resources available at InCor,” reports Professor Dr. João Chang Junior.

This research is one of the few that study the risk of death in cardiac surgeries for people with congenital heart disease. As a result, researchers from InCor-HCFMUSP and the Institut Catholique des Arts et Métiers (Icam) in France created CgntSCORE, a calculator that provides mortality predictions for these patients tailored to the Brazilian context.

Extracted from the InCor cardiac surgery program, the 2,240 data points of patients with congenital heart disease supported the development and validation of the model for the calculator to generate predictions. This will allow healthcare professionals to make more assertive decisions and, in this way, reduce the chances of death.

The next step will be the development of methodologies that result in improved quality of life for congenital heart disease patients undergoing surgery, based on pre-, intra-, and post-operative variables.

“The importance of being a researcher in any field of interest, adapting artificial intelligence methodologies to solve complex problems with a significant volume of information that may or may not affect the outcome of a process, is an important differentiator for professional success today,” states Chang.