Literature DB >> 28372961

Big Data and Machine Learning-Strategies for Driving This Bus: A Summary of the 2016 Intersociety Summer Conference.

Jonathan B Kruskal1, Seth Berkowitz2, J Raymond Geis3, Woojin Kim4, Paul Nagy5, Keith Dreyer6.   

Abstract

The 38th radiology Intersociety Committee reviewed the current state and future direction of clinical data science and its application to radiology practice. The assembled participants discussed the need to use current technology to better generate and demonstrate radiologists' value for our patients and referring providers. The attendants grappled with the potentially disruptive applications of machine learning to image analysis. Although the prospect of algorithms' interpreting images automatically initially shakes the core of the radiology profession, the group emerged with tremendous optimism about the future of radiology. Emerging technologies will provide enormous opportunities for radiologists to augment and improve the quality of care they provide to their patients. Radiologists must maintain an active role in guiding the development of these technologies. The conference ended with a call to action to develop educational strategies for future leaders, communicate optimism for our profession's future, and engage with industry to ensure the ethics and clinical relevance of developing technologies.
Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  ACR; Intersociety Committee; big data; data science; deep learning; imaging informatics; machine learning; radiology

Mesh:

Year:  2017        PMID: 28372961     DOI: 10.1016/j.jacr.2017.02.019

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  12 in total

1.  Deep Learning for Detection of Complete Anterior Cruciate Ligament Tear.

Authors:  Peter D Chang; Tony T Wong; Michael J Rasiej
Journal:  J Digit Imaging       Date:  2019-12       Impact factor: 4.056

Review 2.  Current applications and future directions of deep learning in musculoskeletal radiology.

Authors:  Pauley Chea; Jacob C Mandell
Journal:  Skeletal Radiol       Date:  2019-08-04       Impact factor: 2.199

3.  Fostering a Healthy AI Ecosystem for Radiology: Conclusions of the 2018 RSNA Summit on AI in Radiology.

Authors:  Falgun H Chokshi; Adam E Flanders; Luciano M Prevedello; Curtis P Langlotz
Journal:  Radiol Artif Intell       Date:  2019-03-27

4.  Deep learning and medical imaging.

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

5.  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 6.  Stakeholders' perspectives on the future of artificial intelligence in radiology: a scoping review.

Authors:  Ling Yang; Ioana Cezara Ene; Reza Arabi Belaghi; David Koff; Nina Stein; Pasqualina Lina Santaguida
Journal:  Eur Radiol       Date:  2021-09-21       Impact factor: 5.315

Review 7.  Factors influencing the development of primary care data collection projects from electronic health records: a systematic review of the literature.

Authors:  Marie-Line Gentil; Marc Cuggia; Laure Fiquet; Camille Hagenbourger; Thomas Le Berre; Agnès Banâtre; Eric Renault; Guillaume Bouzille; Anthony Chapron
Journal:  BMC Med Inform Decis Mak       Date:  2017-09-25       Impact factor: 2.796

8.  The Importance of the Clinical Internship for the Radiologist.

Authors:  Andrew D Schweitzer; David Sarkany
Journal:  Acad Radiol       Date:  2020-06-30       Impact factor: 3.173

Review 9.  Artificial intelligence as a medical device in radiology: ethical and regulatory issues in Europe and the United States.

Authors:  Filippo Pesapane; Caterina Volonté; Marina Codari; Francesco Sardanelli
Journal:  Insights Imaging       Date:  2018-08-15

10.  The impact of artificial intelligence in medicine on the future role of the physician.

Authors:  Abhimanyu S Ahuja
Journal:  PeerJ       Date:  2019-10-04       Impact factor: 2.984

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