Artificial intelligence, machine learning, computer-aided diagnosis, and radiomics: advances in imaging towards to precision medicine
Abstract The discipline of radiology and diagnostic imaging has evolved greatly in recent years. We have observed an exponential increase in the number of exams performed, subspecialization of medical fields, and increases in accuracy of the various imaging methods, making it a challenge for the radiologist to “know everything about all exams and regions”. In addition, imaging exams are no longer only qualitative and diagnostic, providing now quantitative information on disease severity, as well as identifying biomarkers of prognosis and treatment response. In view of this, computer-aided diagnosis systems have been developed with the objective of complementing diagnostic imaging and helping the therapeutic decision-making process. With the advent of artificial intelligence, “big data”, and machine learning, we are moving toward the rapid expansion of the use of these tools in daily life of physicians, making each patient unique, as well as leading radiology toward the concept of multidisciplinary approach and precision medicine. In this article, we will present the main aspects of the computational tools currently available for analysis of images and the principles of such analysis, together with the main terms and concepts involved, as well as examining the impact that the development of artificial intelligence has had on radiology and diagnostic imaging.
Main Authors: | Santos,Marcel Koenigkam, Ferreira Júnior,José Raniery, Wada,Danilo Tadao, Tenório,Ariane Priscilla Magalhães, Nogueira-Barbosa,Marcello Henrique, Marques,Paulo Mazzoncini de Azevedo |
---|---|
Format: | Digital revista |
Language: | English |
Published: |
Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem
2019
|
Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842019000600011 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Radiomic analysis of lung cancer for the assessment of patient prognosis and intratumor heterogeneity
by: Ferreira Junior,José Raniery, et al.
Published: (2021) -
Artificial intelligence, radiology, precision medicine, and personalized medicine
by: Leite,Claudia da Costa
Published: (2019) -
Artificial intelligence in medicine
by: Jiménez-Ponce,Fiacro
Published: (2024) -
Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging
by: Faleiros,Matheus Calil, et al.
Published: (2020) -
Progress in medicine and artificial intelligence
by: Viniegra-Velázquez,Leonardo
Published: (2024)