Literature DB >> 29346031

2016 New Horizons Lecture: Beyond Imaging-Radiology of Tomorrow.

Hedvig Hricak1.   

Abstract

This article is based on the New Horizons lecture delivered at the 2016 Radiological Society of North America Annual Meeting. It addresses looming changes for radiology, many of which stem from the disruptive effects of the Fourth Industrial Revolution. This is an emerging era of unprecedented rapid innovation marked by the integration of diverse disciplines and technologies, including data science, machine learning, and artificial intelligence-technologies that narrow the gap between man and machine. Technologic advances and the convergence of life sciences, physical sciences, and bioengineering are creating extraordinary opportunities in diagnostic radiology, image-guided therapy, targeted radionuclide therapy, and radiology informatics, including radiologic image analysis. This article uses the example of oncology to make the case that, if members in the field of radiology continue to be innovative and continuously reinvent themselves, radiology can play an ever-increasing role in both precision medicine and value-driven health care. © RSNA, 2018.

Entities:  

Mesh:

Year:  2018        PMID: 29346031     DOI: 10.1148/radiol.2017171503

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  10 in total

1.  Clinical trials in radiology and data sharing: results from a survey of the European Society of Radiology (ESR) research committee.

Authors:  Maria Bosserdt; Bernd Hamm; Marc Dewey
Journal:  Eur Radiol       Date:  2019-02-27       Impact factor: 5.315

2.  Musculoskeletal radiology: A true companion of the orthopaedic surgeons.

Authors:  Nitin Ghonge; Raju Vaishya
Journal:  J Clin Orthop Trauma       Date:  2019-05-21

3.  Deep learning and medical imaging.

Authors:  Eyal Klang
Journal:  J Thorac Dis       Date:  2018-03       Impact factor: 2.895

4.  Promoting head CT exams in the emergency department triage using a machine learning model.

Authors:  Eyal Klang; Yiftach Barash; Shelly Soffer; Sigalit Bechler; Yehezkel S Resheff; Talia Granot; Moni Shahar; Maximiliano Klug; Gennadiy Guralnik; Eyal Zimlichman; Eli Konen
Journal:  Neuroradiology       Date:  2019-10-10       Impact factor: 2.804

Review 5.  Artificial Intelligence in Interventional Radiology.

Authors:  Joseph R Kallini; John M Moriarty
Journal:  Semin Intervent Radiol       Date:  2022-08-31       Impact factor: 1.780

Review 6.  MRI-guided Radiation Therapy: An Emerging Paradigm in Adaptive Radiation Oncology.

Authors:  Ricardo Otazo; Philippe Lambin; Jean-Philippe Pignol; Mark E Ladd; Heinz-Peter Schlemmer; Michael Baumann; Hedvig Hricak
Journal:  Radiology       Date:  2020-12-22       Impact factor: 11.105

Review 7.  Artificial Intelligence for the Future Radiology Diagnostic Service.

Authors:  Seong K Mun; Kenneth H Wong; Shih-Chung B Lo; Yanni Li; Shijir Bayarsaikhan
Journal:  Front Mol Biosci       Date:  2021-01-28

8.  Artificial intelligence in radiology: does it impact medical students preference for radiology as their future career?

Authors:  Abdulmajeed Bin Dahmash; Mohammed Alabdulkareem; Aljabriyah Alfutais; Ahmed M Kamel; Feras Alkholaiwi; Shaker Alshehri; Yousof Al Zahrani; Mohammed Almoaiqel
Journal:  BJR Open       Date:  2020-12-11

9.  A U-Net Approach to Apical Lesion Segmentation on Panoramic Radiographs.

Authors:  Ibrahim S Bayrakdar; Kaan Orhan; Özer Çelik; Elif Bilgir; Hande Sağlam; Fatma Akkoca Kaplan; Sinem Atay Görür; Alper Odabaş; Ahmet Faruk Aslan; Ingrid Różyło-Kalinowska
Journal:  Biomed Res Int       Date:  2022-01-15       Impact factor: 3.411

10.  A qualitative study to explore opinions of Saudi Arabian radiologists concerning AI-based applications and their impact on the future of the radiology.

Authors:  Walaa Alsharif; Abdulaziz Qurashi; Fadi Toonsi; Ali Alanazi; Fahad Alhazmi; Osamah Abdulaal; Shrooq Aldahery; Khalid Alshamrani
Journal:  BJR Open       Date:  2022-03-21
  10 in total

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