Literature DB >> 31166764

Machine Learning for the Interventional Radiologist.

Ryan D Meek1, Matthew P Lungren2, Judy W Gichoya1.   

Abstract

OBJECTIVE. The purpose of this article is to describe key potential areas of application of machine learning in interventional radiology. CONCLUSION. Machine learning, although in the early stages of development within the field of interventional radiology, has great potential to influence key areas such as image analysis, clinical predictive modeling, and trainee education. A proactive approach from current interventional radiologists and trainees is needed to shape future directions for machine learning and artificial intelligence.

Keywords:  artificial intelligence; interventional radiology; machine learning

Year:  2019        PMID: 31166764     DOI: 10.2214/AJR.19.21527

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  6 in total

1.  Use of Artificial Intelligence in Non-Oncologic Interventional Radiology: Current State and Future Directions.

Authors:  Rohil Malpani; Christopher W Petty; Neha Bhatt; Lawrence H Staib; Julius Chapiro
Journal:  Dig Dis Interv       Date:  2021-07-17

Review 2.  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 3.  Interventional Radiology ex-machina: impact of Artificial Intelligence on practice.

Authors:  Martina Gurgitano; Salvatore Alessio Angileri; Giovanni Maria Rodà; Alessandro Liguori; Marco Pandolfi; Anna Maria Ierardi; Bradford J Wood; Gianpaolo Carrafiello
Journal:  Radiol Med       Date:  2021-04-16       Impact factor: 3.469

Review 4.  Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review.

Authors:  Rebecca Charow; Tharshini Jeyakumar; Sarah Younus; Elham Dolatabadi; Mohammad Salhia; Dalia Al-Mouaswas; Melanie Anderson; Sarmini Balakumar; Megan Clare; Azra Dhalla; Caitlin Gillan; Shabnam Haghzare; Ethan Jackson; Nadim Lalani; Jane Mattson; Wanda Peteanu; Tim Tripp; Jacqueline Waldorf; Spencer Williams; Walter Tavares; David Wiljer
Journal:  JMIR Med Educ       Date:  2021-12-13

Review 5.  Applications and challenges of artificial intelligence in diagnostic and interventional radiology.

Authors:  Joseph Waller; Aisling O'Connor; Eleeza Rafaat; Ahmad Amireh; John Dempsey; Clarissa Martin; Muhammad Umair
Journal:  Pol J Radiol       Date:  2022-02-25

Review 6.  Precision Imaging Guidance in the Era of Precision Oncology: An Update of Imaging Tools for Interventional Procedures.

Authors:  Chiara Floridi; Michaela Cellina; Giovanni Irmici; Alessandra Bruno; Nicolo' Rossini; Alessandra Borgheresi; Andrea Agostini; Federico Bruno; Francesco Arrigoni; Antonio Arrichiello; Roberto Candelari; Antonio Barile; Gianpaolo Carrafiello; Andrea Giovagnoni
Journal:  J Clin Med       Date:  2022-07-12       Impact factor: 4.964

  6 in total

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