Literature DB >> 33666696

To buy or not to buy-evaluating commercial AI solutions in radiology (the ECLAIR guidelines).

Patrick Omoumi1, Alexis Ducarouge2, Antoine Tournier2, Hugh Harvey3, Charles E Kahn4, Fanny Louvet-de Verchère5, Daniel Pinto Dos Santos6, Tobias Kober7, Jonas Richiardi8.   

Abstract

Artificial intelligence (AI) has made impressive progress over the past few years, including many applications in medical imaging. Numerous commercial solutions based on AI techniques are now available for sale, forcing radiology practices to learn how to properly assess these tools. While several guidelines describing good practices for conducting and reporting AI-based research in medicine and radiology have been published, fewer efforts have focused on recommendations addressing the key questions to consider when critically assessing AI solutions before purchase. Commercial AI solutions are typically complicated software products, for the evaluation of which many factors are to be considered. In this work, authors from academia and industry have joined efforts to propose a practical framework that will help stakeholders evaluate commercial AI solutions in radiology (the ECLAIR guidelines) and reach an informed decision. Topics to consider in the evaluation include the relevance of the solution from the point of view of each stakeholder, issues regarding performance and validation, usability and integration, regulatory and legal aspects, and financial and support services. KEY POINTS: • Numerous commercial solutions based on artificial intelligence techniques are now available for sale, and radiology practices have to learn how to properly assess these tools. • We propose a framework focusing on practical points to consider when assessing an AI solution in medical imaging, allowing all stakeholders to conduct relevant discussions with manufacturers and reach an informed decision as to whether to purchase an AI commercial solution for imaging applications. • Topics to consider in the evaluation include the relevance of the solution from the point of view of each stakeholder, issues regarding performance and validation, usability and integration, regulatory and legal aspects, and financial and support services.

Entities:  

Keywords:  Artificial intelligence; Equipment and supplies; Legislation; Software; Workload

Mesh:

Year:  2021        PMID: 33666696     DOI: 10.1007/s00330-020-07684-x

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  11 in total

1.  The Cases for and against Artificial Intelligence in the Medical School Curriculum.

Authors:  Brandon Ngo; Diep Nguyen; Eric vanSonnenberg
Journal:  Radiol Artif Intell       Date:  2022-08-17

2.  European Society of Paediatric Radiology Artificial Intelligence taskforce: a new taskforce for the digital age.

Authors:  Lene Bjerke Laborie; Jaishree Naidoo; Erika Pace; Pierluigi Ciet; Christine Eade; Matthias W Wagner; Thierry A G M Huisman; Susan C Shelmerdine
Journal:  Pediatr Radiol       Date:  2022-06-22

Review 3.  Updates in Artificial Intelligence for Breast Imaging.

Authors:  Manisha Bahl
Journal:  Semin Roentgenol       Date:  2021-12-31       Impact factor: 0.709

Review 4.  Meningioma Radiomics: At the Nexus of Imaging, Pathology and Biomolecular Characterization.

Authors:  Lorenzo Ugga; Gaia Spadarella; Lorenzo Pinto; Renato Cuocolo; Arturo Brunetti
Journal:  Cancers (Basel)       Date:  2022-05-25       Impact factor: 6.575

5.  The impact of radiomics for human papillomavirus status prediction in oropharyngeal cancer: systematic review and radiomics quality score assessment.

Authors:  Gaia Spadarella; Lorenzo Ugga; Giuseppina Calareso; Rossella Villa; Serena D'Aniello; Renato Cuocolo
Journal:  Neuroradiology       Date:  2022-04-23       Impact factor: 2.995

Review 6.  Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction.

Authors:  David Nam; Julius Chapiro; Valerie Paradis; Tobias Paul Seraphin; Jakob Nikolas Kather
Journal:  JHEP Rep       Date:  2022-02-02

7.  Will the EU Medical Device Regulation help to improve the safety and performance of medical AI devices?

Authors:  Emilia Niemiec
Journal:  Digit Health       Date:  2022-03-30

Review 8.  Developing, implementing and governing artificial intelligence in medicine: a step-by-step approach to prevent an artificial intelligence winter.

Authors:  Davy van de Sande; Michel E Van Genderen; Jim M Smit; Joost Huiskens; Jacob J Visser; Robert E R Veen; Edwin van Unen; Oliver Hilgers Ba; Diederik Gommers; Jasper van Bommel
Journal:  BMJ Health Care Inform       Date:  2022-02

Review 9.  Technical and clinical validation of commercial automated volumetric MRI tools for dementia diagnosis-a systematic review.

Authors:  Hugh G Pemberton; Lara A M Zaki; Olivia Goodkin; Ravi K Das; Rebecca M E Steketee; Frederik Barkhof; Meike W Vernooij
Journal:  Neuroradiology       Date:  2021-09-03       Impact factor: 2.804

Review 10.  AI MSK clinical applications: spine imaging.

Authors:  Florian A Huber; Roman Guggenberger
Journal:  Skeletal Radiol       Date:  2021-07-15       Impact factor: 2.199

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