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Verfasst von:Jutzi, Tanja [VerfasserIn]   i
 Krieghoff-Henning, Eva [VerfasserIn]   i
 Holland-Letz, Tim [VerfasserIn]   i
 Utikal, Jochen [VerfasserIn]   i
 Hauschild, Axel [VerfasserIn]   i
 Schadendorf, Dirk [VerfasserIn]   i
 Sondermann, Wiebke [VerfasserIn]   i
 Fröhling, Stefan [VerfasserIn]   i
 Hekler, Achim [VerfasserIn]   i
 Schmitt, Max [VerfasserIn]   i
 Maron, Roman C. [VerfasserIn]   i
 Brinker, Titus Josef [VerfasserIn]   i
Titel:Artificial intelligence in skin cancer diagnostics
Titelzusatz:the patients' perspective
Verf.angabe:Tanja B. Jutzi, Eva Krieghoff-Henning, Tim Holland-Letz, Jochen Sven Utikal, Axel Hauschild, Dirk Schadendorf, Wiebke Sondermann, Stefan Fröhling, Achim Hekler, Max Schmitt, Roman C. Maron and Titus J. Brinker
E-Jahr:2020
Jahr:02 June 2020
Umfang:9 S.
Fussnoten:Gesehen am 02.06.2021
Titel Quelle:Enthalten in: Frontiers in medicine
Ort Quelle:Lausanne : Frontiers Media, 2014
Jahr Quelle:2020
Band/Heft Quelle:7(2020) vom: Juni, Artikel-ID 233, Seite 1-9
ISSN Quelle:2296-858X
Abstract:Background:Artificial intelligence (AI) has shown promise in numerous experimental studies, particularly in skin cancer diagnostics. Translation of these findings into the clinic is the logical next step. This translation can only be successful if patients' concerns and questions are addressed suitably. We therefore conducted a survey to evaluate the patients' view of artificial intelligence in melanoma diagnostics in Germany, with a particular focus on patients with a history of melanoma. Participants and Methods:A web-based questionnaire was designed using LimeSurvey, sent by e-mail to university hospitals and melanoma support groups and advertised on social media. The anonymous questionnaire evaluated patients' expectations and concerns toward artificial intelligence in general as well as their attitudes toward different application scenarios. Descriptive analysis was performed with expression of categorical variables as percentages and 95% confidence intervals. Statistical tests were performed to investigate associations between sociodemographic data and selected items of the questionnaire. Results:298 individuals (154 with a melanoma diagnosis, 143 without) responded to the questionnaire. About 94% [95% CI = 0.91-0.97] of respondents supported the use of artificial intelligence in medical approaches. 88% [95% CI = 0.85-0.92] would even make their own health data anonymously available for the further development of AI-based applications in medicine. Only 41% [95% CI = 0.35-0.46] of respondents were amenable to the use of artificial intelligence as stand-alone system, 94% [95% CI = 0.92-0.97] to its use as assistance system for physicians. In sub-group analyses, only minor differences were detectable. Respondents with a previous history of melanoma were more amenable to the use of AI applications for early detection even at home. They would prefer an application scenario where physician and AI classify the lesions independently. With respect to AI-based applications in medicine, patients were concerned about insufficient data protection, impersonality and susceptibility to errors, but expected faster, more precise and unbiased diagnostics, less diagnostic errors and support for physicians. Conclusions:The vast majority of participants exhibited a positive attitude toward the use of artificial intelligence in melanoma diagnostics, especially as an assistance system.
DOI:doi:10.3389/fmed.2020.00233
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: https://doi.org/10.3389/fmed.2020.00233
 DOI: https://doi.org/10.3389/fmed.2020.00233
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:acceptance
 artificial intelligence
 classification
 dermatologists
 diagnostics
 melanoma
 online survey
 patients view
 share
 skin cancer
K10plus-PPN:1759445843
Verknüpfungen:→ Zeitschrift

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