Artificial intelligence, machine learning, computer-aided diagnosis, and radiomics: advances in imaging towards to precision medicine

Author:

Santos Marcel Koenigkam1ORCID,Ferreira Júnior José Raniery2ORCID,Wada Danilo Tadao1ORCID,Tenório Ariane Priscilla Magalhães1ORCID,Barbosa Marcello Henrique Nogueira1ORCID,Marques Paulo Mazzoncini de Azevedo1ORCID

Affiliation:

1. Universidade de São Paulo, Brazil

2. Universidade de São Paulo, Brazil; Universidade de São Paulo, Brazil

Abstract

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.

Publisher

FapUNIFESP (SciELO)

Subject

Radiology, Nuclear Medicine and imaging

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