dc.contributor.author
Kosan, Esra
dc.contributor.author
Krois, Joachim
dc.contributor.author
Wingenfeld, Katja
dc.contributor.author
Deuter, Christian Eric
dc.contributor.author
Gaudin, Robert
dc.contributor.author
Schwendicke, Falk
dc.date.accessioned
2023-03-23T14:22:51Z
dc.date.available
2023-03-23T14:22:51Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/38539
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-38255
dc.description.abstract
Background: As artificial intelligence (AI) becomes increasingly important in modern dentistry, we aimed to assess patients' perspectives on AI in dentistry specifically for radiographic caries detection and the impact of AI-based diagnosis on patients' trust.
Methods: Validated questionnaires with Likert-scale batteries (1: "strongly disagree" to 5: "strongly agree") were used to query participants' experiences with dental radiographs and their knowledge/attitudes towards AI as well as to assess how AI-based communication of a diagnosis impacted their trust, belief, and understanding. Analyses of variance and ordinal logistic regression (OLR) were used (p < 0.05).
Results: Patients were convinced that "AI is useful" (mean Likert +/- standard deviation 4.2 +/- 0.8) and did not fear AI in general (2.2 +/- 1.0) nor in dentistry (1.6 +/- 0.8). Age, education, and employment status were significantly associated with patients' attitudes towards AI for dental diagnostics. When shown a radiograph with a caries lesion highlighted by an arrow, patients recognized the lesion significantly less often than when using AI-generated coloured overlays highlighting the lesion (p < 0.0005). AI-based communication did not significantly affect patients' trust in dentists' diagnosis (p = 0.44; OLR).
Conclusions: Patients showed a positive attitude towards AI in dentistry. AI-supported diagnostics may assist communicating radiographic findings by increasing patients' ability to recognize caries lesions on dental radiographs.
en
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
artificial intelligence
en
dc.subject
communication
en
dc.subject
dental diagnosis
en
dc.subject
machine learning
en
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und Gesundheit
dc.title
Patients’ Perspectives on Artificial Intelligence in Dentistry: A Controlled Study
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.articlenumber
2143
dcterms.bibliographicCitation.doi
10.3390/jcm11082143
dcterms.bibliographicCitation.journaltitle
Journal of Clinical Medicine
dcterms.bibliographicCitation.number
8
dcterms.bibliographicCitation.originalpublishername
MDPI
dcterms.bibliographicCitation.volume
11
refubium.affiliation
Charité - Universitätsmedizin Berlin
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.bibliographicCitation.pmid
35456236
dcterms.isPartOf.eissn
2077-0383