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 view of this, computer-aided diagnosis systems have been developed with the objective of complementing diagnostic imaging and helping the therapeutic decision-making process. 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. 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”. The discipline of radiology and diagnostic imaging has evolved greatly in recent years.
Keywords: Artificial intelligence Machine learning Computer aided diagnosis Radiomics.ĭescritores: Inteligência artificial Aprendizado de máquina Diagnóstico auxiliado por computador Radiômica.
Artificial intelligence, machine learning, computer-aided diagnosis, and radiomics: advances in imaging towards to precision medicineĪutho(rs): Marcel Koenigkam Santos 1,a José Raniery Ferreira Júnior 2,3,b Danilo Tadao Wada 1,c Ariane Priscilla Magalhães Tenório 3,d Marcello Henrique Nogueira Barbosa 3,e Paulo Mazzoncini de Azevedo Marques 3,f
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