This paper is in the following e-collection/theme issue:

mHealth for Screening (160) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1119) mHealth for Telemedicine and Homecare (281) mHealth for Wellness, Behavior Change and Prevention (2455) Usability of Apps and User Perceptions of mHealth (770) Use and User Demographics of mHealth (284) Mobile Health (mhealth) (2227) Skin Cancer and Melanoma Prevention (93) Innovations and Technology in Cancer Care (330) Innovations and Technology for Cancer Prevention and Screening (122) Mobile Apps for Cancer Care and Cancer Prevention and Screening (173)

Published on in Vol 9 , No 8 (2021) :August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22909, first published .
Digital Natives’ Preferences on Mobile Artificial Intelligence Apps for Skin Cancer Diagnostics: Survey Study

Digital Natives’ Preferences on Mobile Artificial Intelligence Apps for Skin Cancer Diagnostics: Survey Study

Digital Natives’ Preferences on Mobile Artificial Intelligence Apps for Skin Cancer Diagnostics: Survey Study

Authors of this article:

Sarah Haggenmüller 1 Author Orcid Image ;   Eva Krieghoff-Henning 1 Author Orcid Image ;   Tanja Jutzi 1 Author Orcid Image ;   Nicole Trapp 1 Author Orcid Image ;   Lennard Kiehl 1 Author Orcid Image ;   Jochen Sven Utikal 2, 3 Author Orcid Image ;   Sascha Fabian 4 Author Orcid Image ;   Titus Josef Brinker 1 Author Orcid Image
Article Authors Cited by (6) Tweetations (3) Metrics

Journals

  1. Fritsch S, Blankenheim A, Wahl A, Hetfeld P, Maassen O, Deffge S, Kunze J, Rossaint R, Riedel M, Marx G, Bickenbach J. Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients. DIGITAL HEALTH 2022;8:205520762211167 View
  2. Lyu P, Wang Y, Meng Q, Fan P, Ma K, Xiao S, Cao X, Lin G, Dong S. Mapping intellectual structures and research hotspots in the application of artificial intelligence in cancer: A bibliometric analysis. Frontiers in Oncology 2022;12 View
  3. Jutzi T, Krieghoff-Henning E, Brinker T. Künstliche Intelligenz auf dem Vormarsch – Hohe Vorhersage-Genauigkeit bei der Früherkennung pigmentierter Melanome. Aktuelle Dermatologie 2022;48(03):84 View
  4. Jahn A, Navarini A, Cerminara S, Kostner L, Huber S, Kunz M, Maul J, Dummer R, Sommer S, Neuner A, Levesque M, Cheng P, Maul L. Over-Detection of Melanoma-Suspect Lesions by a CE-Certified Smartphone App: Performance in Comparison to Dermatologists, 2D and 3D Convolutional Neural Networks in a Prospective Data Set of 1204 Pigmented Skin Lesions Involving Patients’ Perception. Cancers 2022;14(15):3829 View
  5. Jutzi T, Krieghoff-Henning E, Brinker T. Künstliche Intelligenz auf dem Vormarsch – Hohe Vorhersage-Genauigkeit bei der Früherkennung pigmentierter Melanome. Onkologische Welt 2022;13(05):253 View
  6. Jutzi T, Krieghoff-Henning E, Brinker T. Künstliche Intelligenz auf dem Vormarsch – Hohe Vorhersage-Genauigkeit bei der Früherkennung pigmentierter Melanome. Laryngo-Rhino-Otologie 2022 View