APLICAÇÃO DA INTELIGÊNCIA ARTIFICIAL NA PREDIÇÃO DE PROGNÓSTICOS ONCOLÓGICOS: INOVAÇÕES, OBSTÁCULOS E POSSIBILIDADES PARA A PERSONALIZAÇÃO TERAPÊUTICA

Andreus Cristhian Linhares Andrade; Abner Eliezer Lourenço; Karina Augusta Sarto Nery Franzner; Heitor Bortolucci Pfeil; Roberto Guilherme Rosa Morais; Fabiany Lago Barbosa Hollen; Edilaine Maria Candido de Siqueira Sarra; Gabriella Vieira de Oliveira; Camila Régis Banhara; Emerson Rubens Mendonça Rodrigues; Yuri Plegge Ristow Wippel; Gabrielly Fernandes Costa; Bruna Machado Guim; Victor Vinicius Carvalho Paz; Paula Fernanda Amorim Kirche

APPLICATION OF ARTIFICIAL INTELLIGENCE IN THE PREDICTION OF ONCOLOGICAL PROGNOSIS: INNOVATIONS, OBSTACLES AND POSSIBILITIES FOR THERAPEUTIC PERSONALIZATION

20/12/2024
20/12/2024

Andrade ACL;
Lourenço AE;
Franzner KASN;
Pfeil HB;
Morais RGR;
Hollen FLB;
Sarra EMCS;
de Oliveira GV;
Banhara CR;
Rodrigues ERM;
Wippel YPR;
Costa GF;
Guim BM;
Paz VVC;
Kirche PFA

Keywords

Inteligência Artificial

Artificial Intelligence

Abstract

This systematic review investigates the application of Artificial Intelligence (AI) in the prediction of cancer prognosis, with an emphasis on the personalization of treatments. We analyzed 78 studies that used AI algorithms, such as Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs), in breast, lung, colorectal, and prostate cancers. The main outcomes addressed recurrence, survival, and therapeutic response. The results demonstrated that AI improves accuracy in identifying relapses and predicting treatment response, facilitating personalized interventions. However, the heterogeneity of the data and the lack of standardization represent obstacles to large-scale clinical implementation. The review also highlights the future prospects for integrating AI into precision medicine, favoring the development of more effective and individualized cancer treatments. It is concluded that, although the advances are promising, collaboration between health professionals and AI, the establishment of clear regulations, and the construction of consistent databases are fundamental to the success of AI in oncology.

DOI: https://doi.org/10.56238/sevened2024.039-005

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Copyright (c) 2024 Andreus Cristhian Linhares Andrade, Abner Eliezer Lourenço , Karina Augusta Sarto Nery Franzner, Heitor Bortolucci Pfeil, Roberto Guilherme Rosa Morais, Fabiany Lago Barbosa Hollen, Edilaine Maria Candido de Siqueira Sarra, Gabriella Vieira de Oliveira, Camila Régis Banhara, Emerson Rubens Mendonça Rodrigues, Yuri Plegge Ristow Wippel, Gabrielly Fernandes Costa, Bruna Machado Guim, Victor Vinicius Carvalho Paz, Paula Fernanda Amorim Kirche

CHAPTER 5

Versão (Português (Brasil))

Author(s)

Andreus Cristhian Linhares Andrade
Abner Eliezer Lourenço
Karina Augusta Sarto Nery Franzner
Heitor Bortolucci Pfeil
Roberto Guilherme Rosa Morais
Fabiany Lago Barbosa Hollen
Edilaine Maria Candido de Siqueira Sarra
Gabriella Vieira de Oliveira
Camila Régis Banhara
Emerson Rubens Mendonça Rodrigues
Yuri Plegge Ristow Wippel
Gabrielly Fernandes Costa
Bruna Machado Guim
Victor Vinicius Carvalho Paz
Paula Fernanda Amorim Kirche