Literature DB >> 33354741

The Importance of Incorporating Human Factors in the Design and Implementation of Artificial Intelligence for Skin Cancer Diagnosis in the Real World.

Claire M Felmingham1,2, Nikki R Adler3, Zongyuan Ge4,5,6, Rachael L Morton7, Monika Janda8, Victoria J Mar3,9.   

Abstract

Artificial intelligence (AI) algorithms have been shown to diagnose skin lesions with impressive accuracy in experimental settings. The majority of the literature to date has compared AI and dermatologists as opponents in skin cancer diagnosis. However, in the real-world clinical setting, the clinician will work in collaboration with AI. Existing evidence regarding the integration of such AI diagnostic tools into clinical practice is limited. Human factors, such as cognitive style, personality, experience, preferences, and attitudes may influence clinicians' use of AI. In this review, we consider these human factors and the potential cognitive errors, biases, and unintended consequences that could arise when using an AI skin cancer diagnostic tool in the real world. Integrating this knowledge in the design and implementation of AI technology will assist in ensuring that the end product can be used effectively. Dermatologist leadership in the development of these tools will further improve their clinical relevance and safety.

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Year:  2021        PMID: 33354741     DOI: 10.1007/s40257-020-00574-4

Source DB:  PubMed          Journal:  Am J Clin Dermatol        ISSN: 1175-0561            Impact factor:   7.403


  86 in total

1.  Deep-learning-based, computer-aided classifier developed with a small dataset of clinical images surpasses board-certified dermatologists in skin tumour diagnosis.

Authors:  Y Fujisawa; Y Otomo; Y Ogata; Y Nakamura; R Fujita; Y Ishitsuka; R Watanabe; N Okiyama; K Ohara; M Fujimoto
Journal:  Br J Dermatol       Date:  2018-09-19       Impact factor: 9.302

Review 2.  Artificial Intelligence in Dermatology-Where We Are and the Way to the Future: A Review.

Authors:  Daniel T Hogarty; John C Su; Kevin Phan; Mohamed Attia; Mohammed Hossny; Saeid Nahavandi; Patricia Lenane; Fergal J Moloney; Anousha Yazdabadi
Journal:  Am J Clin Dermatol       Date:  2019-07-05       Impact factor: 7.403

3.  Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.

Authors:  H A Haenssle; C Fink; R Schneiderbauer; F Toberer; T Buhl; A Blum; A Kalloo; A Ben Hadj Hassen; L Thomas; A Enk; L Uhlmann
Journal:  Ann Oncol       Date:  2018-08-01       Impact factor: 32.976

4.  Artificial intelligence for melanoma diagnosis: how can we deliver on the promise?

Authors:  V J Mar; H P Soyer
Journal:  Ann Oncol       Date:  2018-08-01       Impact factor: 32.976

Review 5.  Melanoma.

Authors:  Dirk Schadendorf; Alexander C J van Akkooi; Carola Berking; Klaus G Griewank; Ralf Gutzmer; Axel Hauschild; Andreas Stang; Alexander Roesch; Selma Ugurel
Journal:  Lancet       Date:  2018-09-15       Impact factor: 79.321

6.  Dermatologist-level classification of skin cancer with deep neural networks.

Authors:  Andre Esteva; Brett Kuprel; Roberto A Novoa; Justin Ko; Susan M Swetter; Helen M Blau; Sebastian Thrun
Journal:  Nature       Date:  2017-01-25       Impact factor: 49.962

7.  Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks.

Authors:  Philipp Tschandl; Cliff Rosendahl; Bengu Nisa Akay; Giuseppe Argenziano; Andreas Blum; Ralph P Braun; Horacio Cabo; Jean-Yves Gourhant; Jürgen Kreusch; Aimilios Lallas; Jan Lapins; Ashfaq Marghoob; Scott Menzies; Nina Maria Neuber; John Paoli; Harold S Rabinovitz; Christoph Rinner; Alon Scope; H Peter Soyer; Christoph Sinz; Luc Thomas; Iris Zalaudek; Harald Kittler
Journal:  JAMA Dermatol       Date:  2019-01-01       Impact factor: 10.282

8.  Melanoma staging: Evidence-based changes in the American Joint Committee on Cancer eighth edition cancer staging manual.

Authors:  Jeffrey E Gershenwald; Richard A Scolyer; Kenneth R Hess; Vernon K Sondak; Georgina V Long; Merrick I Ross; Alexander J Lazar; Mark B Faries; John M Kirkwood; Grant A McArthur; Lauren E Haydu; Alexander M M Eggermont; Keith T Flaherty; Charles M Balch; John F Thompson
Journal:  CA Cancer J Clin       Date:  2017-10-13       Impact factor: 508.702

Review 9.  A guide to deep learning in healthcare.

Authors:  Andre Esteva; Alexandre Robicquet; Bharath Ramsundar; Volodymyr Kuleshov; Mark DePristo; Katherine Chou; Claire Cui; Greg Corrado; Sebastian Thrun; Jeff Dean
Journal:  Nat Med       Date:  2019-01-07       Impact factor: 53.440

10.  Automated decision support in melanocytic lesion management.

Authors:  Stephen J Gilmore
Journal:  PLoS One       Date:  2018-09-07       Impact factor: 3.240

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  5 in total

Review 1.  Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.

Authors:  Baptiste Vasey; Myura Nagendran; Bruce Campbell; David A Clifton; Gary S Collins; Spiros Denaxas; Alastair K Denniston; Livia Faes; Bart Geerts; Mudathir Ibrahim; Xiaoxuan Liu; Bilal A Mateen; Piyush Mathur; Melissa D McCradden; Lauren Morgan; Johan Ordish; Campbell Rogers; Suchi Saria; Daniel S W Ting; Peter Watkinson; Wim Weber; Peter Wheatstone; Peter McCulloch
Journal:  Nat Med       Date:  2022-05-18       Impact factor: 87.241

2.  Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.

Authors:  Baptiste Vasey; Myura Nagendran; Bruce Campbell; David A Clifton; Gary S Collins; Spiros Denaxas; Alastair K Denniston; Livia Faes; Bart Geerts; Mudathir Ibrahim; Xiaoxuan Liu; Bilal A Mateen; Piyush Mathur; Melissa D McCradden; Lauren Morgan; Johan Ordish; Campbell Rogers; Suchi Saria; Daniel S W Ting; Peter Watkinson; Wim Weber; Peter Wheatstone; Peter McCulloch
Journal:  BMJ       Date:  2022-05-18

3.  General Practitioners' Attitudes Toward Artificial Intelligence-Enabled Systems: Interview Study.

Authors:  Christoph Buck; Eileen Doctor; Jasmin Hennrich; Jan Jöhnk; Torsten Eymann
Journal:  J Med Internet Res       Date:  2022-01-27       Impact factor: 5.428

Review 4.  Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review.

Authors:  Onur Asan; Avishek Choudhury
Journal:  JMIR Hum Factors       Date:  2021-06-18

Review 5.  Human Factors and Technological Characteristics Influencing the Interaction of Medical Professionals With Artificial Intelligence-Enabled Clinical Decision Support Systems: Literature Review.

Authors:  Michael Knop; Sebastian Weber; Marius Mueller; Bjoern Niehaves
Journal:  JMIR Hum Factors       Date:  2022-03-24
  5 in total

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