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Részletek

A cikk állandó MOB linkje:
http://mob.gyemszi.hu/detailsperm.jsp?PERMID=157541
MOB:2022/4
Szerzők:Fazekas Szuzina; Budai Bettina Katalin; Stollmayer Róbert; Novák Kaposi Pál; Bérczi Viktor
Tárgyszavak:EGÉSZSÉGÜGYI INFORMATIKA ALKALMAZÁSI TERÜLETEI; RADIOLÓGIA; MODELLEK, NEUROLÓGIAI
Folyóirat:Imaging - 2022. 14. évf. 2. sz.
[https://akjournals.com/view/journals/1647/1647-overview.xml ]


  Artificial intelligence and neural networks in radiology - Basics that all radiology residents should know / Szuzina Fazekas [et al.]
  Bibliogr.: p. 80-81. - Abstr. eng. - DOI: https://doi.org/10.1556/1647.2022.00104
  In: Imaging. - ISSN eISSN 2732-0960. - 2022. 14. évf. 2. sz., p. 73-81. : ill.


The area of Artificial Intelligence is developing at a high rate. In the medical field, an extreme amount of data is created every day. As the images and the reports are quantifiable, the field of radiology aspires to deliver better, more efficient clinical care. Artificial intelligence (AI) means the simulation of human intelligence by a system or machine. It has been developed to enable machines to "think", which means to be able to learn, reason, predict, categorize, and solve problems concerning high amounts of data and make decisions in a more effective manner than before. Different AI methods can help radiologists with pre-screening images and identifying features. In this review, we summarize the basic concepts which are needed to understand AI. As the AI methods are expected to exceed the threshold for clinical usefulness soon, in the near future it will be inevitable to use AI in medicine.  Kulcsszavak: artificial intelligence, machine learning, neural networks, image classification, object detection, segmentation