Trust Me, I´m a Doctor - User Perceptions of AI-Driven Apps for Mobile Health Diagnosis

Matthias Baldauf (Vortragende:r), Peter Fröhlich, Rainer Endl

Publikation: Beitrag in Buch oder TagungsbandVortrag mit Beitrag in TagungsbandBegutachtung

Abstract

First consumer-facing apps for medical self-diagnosis through Artificial Intelligence have hit the market only recently. These promise to detect malicious skin changes from photos or respiratory diseases from cough noises captured by the smartphone microphone, for example. While there is a large body of research on HCI-related aspects of mobile health applications, knowledge about the user perceptions of such novel AI-driven self-diagnosis apps and factors affecting their acceptance and adoption is scarce. In an online survey, we investigated the participants´ overall willingness-to-use (considering four types of captured and processed data) and identified trust factors and desirable features. We found that more than half of the participants would use AI-driven self-diagnosis apps, yet mainly integrated into prevailing general practitioner care. Based on the results, we draw conclusions which can guide the design, development, and launch of AI-driven self-diagnosis apps.
OriginalspracheEnglisch
TitelProceedings 19th International Conference on Mobile and Ubiquitous Multimedia (MUM 2020)
Seiten167-178
Seitenumfang12
DOIs
PublikationsstatusVeröffentlicht - 2020
VeranstaltungMUM2020 - 19th International Conference on Mobile and Ubiquitous Multimedia -
Dauer: 22 Nov. 202025 Nov. 2020

Konferenz

KonferenzMUM2020 - 19th International Conference on Mobile and Ubiquitous Multimedia
Zeitraum22/11/2025/11/20

Research Field

  • Ehemaliges Research Field - Capturing Experience

Schlagwörter

  • mhealth
  • health assessment
  • self-diagnosis
  • artificial intelligence

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