SWS Academic Research eLibrarySocial Sciences & Art

Scholarly record

APPLICATION OF NEW TECHNOLOGIES IN THE RADIOLOGY MARKET – DIRECTIONS OF DEVELOPMENT, OPPORTUNITIES, AND THREATS

Piotr Kardasz, Krzysztof Kolebski, Simeon Iliev, Georgi Kadikyanov

First published: 2025https://doi.org/10.35603/sws.iscss.2025/s07.92View metrics

Abstract

Radiology, a field continually evolving is currently experiencing transformative advancements. This paper explores the present state and future projections of the radiology market, emphasizing the role of artificial intelligence (AI) and virtual reality (VR). With the proliferation of diagnostic equipment and increasing examination numbers, the radiology market demonstrates substantial growth potential. Projections indicate a surpassing of $12 billion for the MRI market by 2030. AI, particularly through machine learning algorithms, offers rapid, precise diagnoses, reshaping radiologists' workflows and decision-making processes. VR technologies enhance education and training, providing immersive learning experiences for medical students and professionals. While AI promises efficiency and enhanced patient care, it also poses threats such as job displacement and challenges in data management. Adapting to these technologies will be essential for radiologists. In conclusion, the radiology market is poised for expansion, driven by AI and VR innovations. However, careful consideration of implications, including workforce dynamics and data management, is necessary to ensure sustainable progress in the field.

Publication Impact Profile

Publication details

Title
APPLICATION OF NEW TECHNOLOGIES IN THE RADIOLOGY MARKET – DIRECTIONS OF DEVELOPMENT, OPPORTUNITIES, AND THREATS
Authors
Piotr Kardasz, Krzysztof Kolebski, Simeon Iliev, Georgi Kadikyanov
Proceedings
Proceedings of 12th SWS International Scientific Conference on Social Sciences - ISCSS 2025
Publisher
SGEM WORLD SCIENCE (SWS) Scholarly Society
Year
2025
Pages
769-774
SWS Citekey
Kardasz202511769774
ISSN
2682-9959
ISBN
978-3-903438-16-3
Language
en
Publication type
Proceedings Paper
Keywords
References11
  1. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Healthcare_ resou rce_statistics_- _technical_resources_ and_medical_technology &oldid= 452031# Availability_of_medical_technology [08.05.2024]

  2. Naczelna Izba Lekarska, Zestawienie liczbowe lekarzy i lekarzy dentystГіw wg dziedziny i stopnia specjalizacji z uwzglednieniem podzialu na lekarzy wykonujacych i nie wykonujacych zawodu, s. 3, chrome-exten-sion://efaidnbmnnnibpca jpcglclefindmkaj/https://nil.org.pl/uploaded_files/1712308352_stat-4.pdf [08.05.2024]

  3. chrome-exten-sion://efaidnbmnnnibpcajpcglclefindmkaj/https:// www.bundesae rzte kammer.de/fileadmin/user_upload/BAEK/Ueber_uns/Statistik/AErztestatistik_2023_18.04.2024.pdf s. 4 [08.05.2024]

  4. P. Lajczak i in., Zastosowanie symulatora VR Eyesi w szkoleniach operacji zacmy, Inno-wacje w medycynie - przeglad wybranych technologii XXI w., Tom 12, 2023

  5. W. Gan, Researching the application of virtual reality in medical education: one-year fol-low-up of a randomized trial, „BMC Medical Education” 23, 2023, nr 3, s. 9-10.

  6. https://www.linkedin.com/company/vrmed3d-sp-z-o-o?trk=affiliated-pages [08.05. 2024]

  7. Hosny, A., Parmar, C., Quackenbush, J., Schwartz, L. H., & Aerts, H. J. W. L. (2018). Artificial intelligence in radiology. Nature Reviews Cancer, 18(8), 500–510. DOI: 10.1038/s41568-018-0016-5

  8. Pianykh, O. S., Langs, G., Dewey, M., Enzmann, D. R., Herold, C. J., Schoenberg, S. O., & Brink, J. A. (2020). Continuous Learning AI in Radiology: Implementation Principles and Early Applications. Radiology, 297(1), 6–14. DOI: 10.1148/radiol.2020200038

  9. The British Institute of Radiology, World Partner Network, The Global Future Of Imag-ing, 2019.

  10. Chockley, K., & Emanuel, E., The End of Radiology? Three Threats to the Future Prac-tice of Radiology. Journal of the American College of Radiology, 2016.

  11. Monika K. Andrych-Zalewska, Zdzislaw Chlopek, Jerzy Merkisz, Jacek Pielecha. Comparison of gasoline engine exhaust emissions of a passenger car through the WLTC and RDE type approval tests. Energies. 2022, vol. 15, nr 21, art. 8157, s. 1-13.

View or Download full articleAccess options
Full paper accessChoose SWS login, librarian support, or instant article download.

SWS access login

Login as SWS Scientific Committee

Authors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.

For librarian assistance: [email protected]

Purchase Instant Access

48-hour online accessComing soon
Online-only accessComing soon
Download the full article in PDF formatEUR 35
  • Article can be downloaded after successful payment.
  • Article may be used according to SWS library access terms.
  • Article cannot be redistributed.
Get full paper

Back to publication list