Literature DB >> 33664367

A survey of clinicians on the use of artificial intelligence in ophthalmology, dermatology, radiology and radiation oncology.

Jane Scheetz1, Philip Rothschild1,2, Myra McGuinness1,3, Xavier Hadoux1, H Peter Soyer4,5, Monika Janda6, James J J Condon7,8, Luke Oakden-Rayner7,8, Lyle J Palmer7,8, Stuart Keel1, Peter van Wijngaarden9,10.   

Abstract

Artificial intelligence technology has advanced rapidly in recent years and has the potential to improve healthcare outcomes. However, technology uptake will be largely driven by clinicians, and there is a paucity of data regarding the attitude that clinicians have to this new technology. In June-August 2019 we conducted an online survey of fellows and trainees of three specialty colleges (ophthalmology, radiology/radiation oncology, dermatology) in Australia and New Zealand on artificial intelligence. There were 632 complete responses (n = 305, 230, and 97, respectively), equating to a response rate of 20.4%, 5.1%, and 13.2% for the above colleges, respectively. The majority (n = 449, 71.0%) believed artificial intelligence would improve their field of medicine, and that medical workforce needs would be impacted by the technology within the next decade (n = 542, 85.8%). Improved disease screening and streamlining of monotonous tasks were identified as key benefits of artificial intelligence. The divestment of healthcare to technology companies and medical liability implications were the greatest concerns. Education was identified as a priority to prepare clinicians for the implementation of artificial intelligence in healthcare. This survey highlights parallels between the perceptions of different clinician groups in Australia and New Zealand about artificial intelligence in medicine. Artificial intelligence was recognized as valuable technology that will have wide-ranging impacts on healthcare.

Entities:  

Year:  2021        PMID: 33664367      PMCID: PMC7933437          DOI: 10.1038/s41598-021-84698-5

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  28 in total

Review 1.  Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery.

Authors:  Shane O'Sullivan; Nathalie Nevejans; Colin Allen; Andrew Blyth; Simon Leonard; Ugo Pagallo; Katharina Holzinger; Andreas Holzinger; Mohammed Imran Sajid; Hutan Ashrafian
Journal:  Int J Med Robot       Date:  2019-02       Impact factor: 2.547

2.  Selecting for a sustainable workforce to meet the future healthcare needs of rural communities in Australia.

Authors:  M Hay; A M Mercer; I Lichtwark; S Tran; W C Hodgson; H T Aretz; E G Armstrong; D Gorman
Journal:  Adv Health Sci Educ Theory Pract       Date:  2016-11-01       Impact factor: 3.853

3.  The End of Radiology? Three Threats to the Future Practice of Radiology.

Authors:  Katie Chockley; Ezekiel Emanuel
Journal:  J Am Coll Radiol       Date:  2016-09-18       Impact factor: 5.532

4.  Man against machine reloaded: performance of a market-approved convolutional neural network in classifying a broad spectrum of skin lesions in comparison with 96 dermatologists working under less artificial conditions.

Authors:  H A Haenssle; C Fink; F Toberer; J Winkler; W Stolz; T Deinlein; R Hofmann-Wellenhof; A Lallas; S Emmert; T Buhl; M Zutt; A Blum; M S Abassi; L Thomas; I Tromme; P Tschandl; A Enk; A Rosenberger
Journal:  Ann Oncol       Date:  2020-01       Impact factor: 32.976

5.  Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

Authors:  Zhixi Li; Yifan He; Stuart Keel; Wei Meng; Robert T Chang; Mingguang He
Journal:  Ophthalmology       Date:  2018-03-02       Impact factor: 12.079

6.  An Automated Grading System for Detection of Vision-Threatening Referable Diabetic Retinopathy on the Basis of Color Fundus Photographs.

Authors:  Zhixi Li; Stuart Keel; Chi Liu; Yifan He; Wei Meng; Jane Scheetz; Pei Ying Lee; Jonathan Shaw; Daniel Ting; Tien Yin Wong; Hugh Taylor; Robert Chang; Mingguang He
Journal:  Diabetes Care       Date:  2018-10-01       Impact factor: 19.112

Review 7.  High-performance medicine: the convergence of human and artificial intelligence.

Authors:  Eric J Topol
Journal:  Nat Med       Date:  2019-01-07       Impact factor: 53.440

8.  Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging.

Authors:  Martin Halicek; Guolan Lu; James V Little; Xu Wang; Mihir Patel; Christopher C Griffith; Mark W El-Deiry; Amy Y Chen; Baowei Fei
Journal:  J Biomed Opt       Date:  2017-06-01       Impact factor: 3.170

9.  Artificial intelligence in radiology: friend or foe? Where are we now and where are we heading?

Authors:  Emre Pakdemirli
Journal:  Acta Radiol Open       Date:  2019-02-21

10.  Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey.

Authors:  Cherry Sit; Rohit Srinivasan; Ashik Amlani; Keerthini Muthuswamy; Aishah Azam; Leo Monzon; Daniel Stephen Poon
Journal:  Insights Imaging       Date:  2020-02-05
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  14 in total

1.  Impact of artificial intelligence on pathologists' decisions: an experiment.

Authors:  Julien Meyer; April Khademi; Bernard Têtu; Wencui Han; Pria Nippak; David Remisch
Journal:  J Am Med Inform Assoc       Date:  2022-09-12       Impact factor: 7.942

Review 2.  Harnessing the Power of Artificial Intelligence in Otolaryngology and the Communication Sciences.

Authors:  Blake S Wilson; Debara L Tucci; David A Moses; Edward F Chang; Nancy M Young; Fan-Gang Zeng; Nicholas A Lesica; Andrés M Bur; Hannah Kavookjian; Caroline Mussatto; Joseph Penn; Sara Goodwin; Shannon Kraft; Guanghui Wang; Jonathan M Cohen; Geoffrey S Ginsburg; Geraldine Dawson; Howard W Francis
Journal:  J Assoc Res Otolaryngol       Date:  2022-04-20

3.  Promoting Research, Awareness, and Discussion on AI in Medicine Using #MedTwitterAI: A Longitudinal Twitter Hashtag Analysis.

Authors:  Faisal A Nawaz; Austin A Barr; Monali Y Desai; Christos Tsagkaris; Romil Singh; Elisabeth Klager; Fabian Eibensteiner; Emil D Parvanov; Mojca Hribersek; Maria Kletecka-Pulker; Harald Willschke; Atanas G Atanasov
Journal:  Front Public Health       Date:  2022-07-01

Review 4.  Exploring stakeholder attitudes towards AI in clinical practice.

Authors:  Ian A Scott; Stacy M Carter; Enrico Coiera
Journal:  BMJ Health Care Inform       Date:  2021-12

Review 5.  Perceptions and Needs of Artificial Intelligence in Health Care to Increase Adoption: Scoping Review.

Authors:  Han Shi Jocelyn Chew; Palakorn Achananuparp
Journal:  J Med Internet Res       Date:  2022-01-14       Impact factor: 5.428

6.  Factors Influencing Clinician Trust in Predictive Clinical Decision Support Systems for In-Hospital Deterioration: Qualitative Descriptive Study.

Authors:  Jessica M Schwartz; Maureen George; Sarah Collins Rossetti; Patricia C Dykes; Simon R Minshall; Eugene Lucas; Kenrick D Cato
Journal:  JMIR Hum Factors       Date:  2022-05-12

7.  Perceptions of Canadian vascular surgeons toward artificial intelligence and machine learning.

Authors:  Ben Li; Charles de Mestral; Muhammad Mamdani; Mohammed Al-Omran
Journal:  J Vasc Surg Cases Innov Tech       Date:  2022-07-19

8.  Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients.

Authors:  Sebastian J Fritsch; Andrea Blankenheim; Alina Wahl; Petra Hetfeld; Oliver Maassen; Saskia Deffge; Julian Kunze; Rolf Rossaint; Morris Riedel; Gernot Marx; Johannes Bickenbach
Journal:  Digit Health       Date:  2022-08-08

9.  A Survey on the Use of Artificial Intelligence by Clinicians in Dentistry and Oral and Maxillofacial Surgery.

Authors:  Tim Eschert; Falk Schwendicke; Joachim Krois; Lauren Bohner; Shankeeth Vinayahalingam; Marcel Hanisch
Journal:  Medicina (Kaunas)       Date:  2022-08-05       Impact factor: 2.948

10.  The Future of Precision Prevention for Advanced Melanoma.

Authors:  Katie J Lee; Brigid Betz-Stablein; Mitchell S Stark; Monika Janda; Aideen M McInerney-Leo; Liam J Caffery; Nicole Gillespie; Tatiane Yanes; H Peter Soyer
Journal:  Front Med (Lausanne)       Date:  2022-01-17
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