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Caffery LJ, Janda M, Miller R, Abbott LM, Arnold C, Caccetta T, Guitera P, Shumack S, Fernández-Peñas P, Mar V, Soyer HP. Informing a position statement on the use of artificial intelligence in dermatology in Australia. Australas J Dermatol 2023; 64:e11-e20. [PMID: 36380357 DOI: 10.1111/ajd.13946] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 10/06/2022] [Accepted: 10/17/2022] [Indexed: 11/17/2022]
Abstract
Artificial Intelligence (AI) is the ability for computers to simulate human intelligence. In dermatology, there is substantial interest in using AI to identify skin lesions from images. Due to increasing research and interest in the use of AI, the Australasian College of Dermatologists has developed a position statement to inform its members of appropriate use of AI. This article presents the ACD Position Statement on the use of AI in dermatology, and provides explanatory information that was used to inform the development of this statement.
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Affiliation(s)
- Liam J Caffery
- Centre for Online Health, The University of Queensland, Brisbane, Queensland, Australia.,Centre for Health Services Research, The University of Queensland, Brisbane, Queensland, Australia.,The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, Queensland, Australia
| | - Monika Janda
- Centre for Health Services Research, The University of Queensland, Brisbane, Queensland, Australia
| | - Robert Miller
- The Australasian College of Dermatologists, Sydney, New South Wales, Australia
| | - Lisa M Abbott
- The Australasian College of Dermatologists, Sydney, New South Wales, Australia.,Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
| | - Chris Arnold
- The Australasian College of Dermatologists, Sydney, New South Wales, Australia.,Australasian Society of Cosmetic Dermatologists, South Yarra, Victoria, Australia.,BioGrid Australia, Parkville, Victoria, Australia
| | - Tony Caccetta
- The Australasian College of Dermatologists, Sydney, New South Wales, Australia
| | - Pascale Guitera
- The Australasian College of Dermatologists, Sydney, New South Wales, Australia
| | - Stephen Shumack
- The Australasian College of Dermatologists, Sydney, New South Wales, Australia.,The University of Sydney, Sydney, New South Wales, Australia
| | - Pablo Fernández-Peñas
- The Australasian College of Dermatologists, Sydney, New South Wales, Australia.,The University of Sydney, Sydney, New South Wales, Australia
| | - Victoria Mar
- The Australasian College of Dermatologists, Sydney, New South Wales, Australia.,Victorian Melanoma Service, Alfred Health, Victoria, Australia.,School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - H Peter Soyer
- The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, Queensland, Australia
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Giansanti D, Di Basilio F. The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus. Healthcare (Basel) 2022; 10:509. [PMID: 35326987 PMCID: PMC8949694 DOI: 10.3390/healthcare10030509] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 03/03/2022] [Accepted: 03/08/2022] [Indexed: 12/27/2022] Open
Abstract
Artificial intelligence is having important developments in the world of digital radiology also thanks to the boost given to the research sector by the COVID-19 pandemic. In the last two years, there was an important development of studies focused on both challenges and acceptance and consensus in the field of Artificial Intelligence. The challenges and acceptance and consensus are two strategic aspects in the development and integration of technologies in the health domain. The study conducted two narrative reviews by means of two parallel points of view to take stock both on the ongoing challenges and on initiatives conducted to face the acceptance and consensus in this area. The methodology of the review was based on: (I) search of PubMed and Scopus and (II) an eligibility assessment, using parameters with 5 levels of score. The results have: (a) highlighted and categorized the important challenges in place. (b) Illustrated the different types of studies conducted through original questionnaires. The study suggests for future research based on questionnaires a better calibration and inclusion of the challenges in place together with validation and administration paths at an international level.
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Data Sharing of Imaging in an Evolving Health Care World: Report of the ACR Data Sharing Workgroup Part 2: Annotation, Curation, and Contracting. J Am Coll Radiol 2021; 18:1655-1665. [PMID: 34607753 DOI: 10.1016/j.jacr.2021.07.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 07/12/2021] [Indexed: 12/29/2022]
Abstract
A core principle of ethical data sharing is maintaining the security and anonymity of the data, and care must be taken to ensure medical records and images cannot be reidentified to be traced back to patients or misconstrued as a breach in the trust between health care providers and patients. Once those principles have been observed, those seeking to share data must take the appropriate steps to curate the data in a way that organizes the clinically relevant information so as to be useful to the data sharing party, assesses the ensuing value of the data set and its annotations, and informs the data sharing contracts that will govern use of the data. Embarking on a data sharing partnership engenders a host of ethical, practical, technical, legal, and commercial challenges that require a thoughtful, considered approach. In 2019 the ACR convened a Data Sharing Workgroup to develop philosophies around best practices in the sharing of health information. This is Part 2 of a Report on the workgroup's efforts in exploring these issues.
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