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Pregled bibliografske jedinice broj: 1070003

Artificial Intelligence in Radiology


Filipović-Grčić, Luka; Đerke, Filip
Artificial Intelligence in Radiology // Rad Hrvatske akademije znanosti i umjetnosti. Medicinske znanosti, 531 (2019), 55-59 doi:10.21857/y26kec3o79 (domaća recenzija, pregledni rad, stručni)


CROSBI ID: 1070003 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Artificial Intelligence in Radiology

Autori
Filipović-Grčić, Luka ; Đerke, Filip

Izvornik
Rad Hrvatske akademije znanosti i umjetnosti. Medicinske znanosti (1848-641X) 531 (2019); 55-59

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, pregledni rad, stručni

Ključne riječi
artificial intelligence, radiology, deep learning, neural networks, radiomics, clinical application of artificial intelligence

Sažetak
Since its first use in medical purpose in the 1960s, the concept of artificial intelligence has been especially appealing to health care, particularly radiology. With the development of ever more powerful computers from the 1990s to the present, various forms of artificial intelligence have found their way into different medical specialties – most notably radiology, dermatology, ophthalmology, and pathology. Due to the growing presence of such systems, it is paramount for the specialists handling them to get acquainted with them in order to provide the best service for their patients. It is therefore the aim of this article to explain the most basic principles of artificial intelligence, accentuating the most prominent concepts used in radiology today, such as deep learning and neural networks. It will also mention some of the artificial intelligence systems approved for clinical use in the US, such as IDx-DR, used to discover more than mild diabetic retinopathy in patients over 22 years of age ; and Arterys, used for cardiac segmentation and discovering liver and lung nodules. Same as in many other fields, there is a constant need for improvement – in construction, testing, and application of these new technologies. Many ethical questions are asked, considering privacy and liability of artificial intelligence systems in clinical use. One of the greatest concerns for radiologists is the possibility of being replaced by these systems. This scenario seems to be far-fetched, at least for the time being. Radiologists should use that time to get to know the “enemy”. If they accomplish this, they might discover that they had had an ally all along.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Kliničke medicinske znanosti, Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove:
Klinički bolnički centar Zagreb

Profili:

Avatar Url Filip Đerke (autor)

Avatar Url LUKA Filipović-Grčić (autor)

Poveznice na cjeloviti tekst rada:

doi hrcak.srce.hr dizbi.hazu.hr

Citiraj ovu publikaciju:

Filipović-Grčić, Luka; Đerke, Filip
Artificial Intelligence in Radiology // Rad Hrvatske akademije znanosti i umjetnosti. Medicinske znanosti, 531 (2019), 55-59 doi:10.21857/y26kec3o79 (domaća recenzija, pregledni rad, stručni)
Filipović-Grčić, L. & Đerke, F. (2019) Artificial Intelligence in Radiology. Rad Hrvatske akademije znanosti i umjetnosti. Medicinske znanosti, 531, 55-59 doi:10.21857/y26kec3o79.
@article{article, author = {Filipovi\'{c}-Gr\v{c}i\'{c}, Luka and \DJerke, Filip}, year = {2019}, pages = {55-59}, DOI = {10.21857/y26kec3o79}, keywords = {artificial intelligence, radiology, deep learning, neural networks, radiomics, clinical application of artificial intelligence}, journal = {Rad Hrvatske akademije znanosti i umjetnosti. Medicinske znanosti}, doi = {10.21857/y26kec3o79}, volume = {531}, issn = {1848-641X}, title = {Artificial Intelligence in Radiology}, keyword = {artificial intelligence, radiology, deep learning, neural networks, radiomics, clinical application of artificial intelligence} }
@article{article, author = {Filipovi\'{c}-Gr\v{c}i\'{c}, Luka and \DJerke, Filip}, year = {2019}, pages = {55-59}, DOI = {10.21857/y26kec3o79}, keywords = {artificial intelligence, radiology, deep learning, neural networks, radiomics, clinical application of artificial intelligence}, journal = {Rad Hrvatske akademije znanosti i umjetnosti. Medicinske znanosti}, doi = {10.21857/y26kec3o79}, volume = {531}, issn = {1848-641X}, title = {Artificial Intelligence in Radiology}, keyword = {artificial intelligence, radiology, deep learning, neural networks, radiomics, clinical application of artificial intelligence} }

Uključenost u ostale bibliografske baze podataka::


  • EBSCO
  • Google Scholar
  • Hrvatski arhiv weba


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