Non-Cochrane · DTA · PM42824956
Diagnostic Efficiency of Artificial Intelligence Integrated Intraoral Mobile Photographs in Identification of Oral Potentially Malignant Disorders: An Umbrella Review.
Kumar P D Madan, Lavanya C, Sivakumar Sasidharan, et al. · International journal of dentistry · 2026 · PubMed · doi:10.1155/ijod/6654212
Findings
Population People assessed for oral potentially malignant disorders and oral mucosal lesions
2 findings
| AI-assisted intraoral mobile photographs | Conventional diagnostic reference standards, including histopathology | Specificity for detecting oral potentially malignant disorders | Specificity 0.89 [0.86, 0.92] GRADE not reported 5 studies |
| AI-assisted intraoral mobile photographs | Conventional diagnostic reference standards, including histopathology | Sensitivity for detecting oral potentially malignant disorders | Sensitivity 0.907 [0.888, 0.926] GRADE not reported 6 studies |
Included primary studies 6
Open in Studies| Study | Year | Also included by | Outcomes it informs here | Trial data |
|---|---|---|---|---|
| Kim 2022 Efficacy of Artificial Intelligence-Assisted Discrimination of Oral Cancerous Lesions from Normal Mucosa Based on the Oral Mucosal Image:… PMID:35884560 | 2022 | 2 other reviews | not stated | not extracted yet |
| Li 2024 Diagnostic accuracy of artificial intelligence assisted clinical imaging in the detection of oral potentially malignant disorders and oral… PMID:38652301 | 2024 | 2 other reviews | not stated | not extracted yet |
| Sahoo 2024 Diagnostic performance of artificial intelligence in detecting oral potentially malignant disorders and oral cancer using medical… PMID:39568787 | 2024 | 1 other review | not stated | not extracted yet |
| Ferro 2022 Machine learning in point-of-care automated classification of oral potentially malignant and malignant disorders: a systematic review and… PMID:35963880 | 2022 | this review only | Sensitivity for detecting oral potentially malignant disorders | not extracted yet |
| Rokhshad 2024 Artificial intelligence for classification and detection of oral mucosa lesions on photographs: a systematic review and meta-analysis. PMID:38217733 | 2024 | this review only | not stated | not extracted yet |
| Uhrin 2023 Teledentistry: A Future Solution in the Diagnosis of Oral Lesions: Diagnostic Meta-Analysis and Systematic Review. PMID:36976779 | 2023 | this review only | not stated | not extracted yet |
Overlap with other reviews
Reviews that include the same primary studies are not independent evidence. Shared counts match studies by PMID, DOI or NCT, and otherwise by author and year (a probable match). Only the non-Cochrane dental reviews have study lists, so overlap with Cochrane reviews is not counted yet.
Review question
| Element | Planned (methods) | Found (results) |
|---|---|---|
| Population | Human participants with clinically or histologically diagnosed OPMDs | People with OPMDs and other oral mucosal lesions (n=6 systematic reviews; sample sizes 200 to 400 per Table 2; text states 120 to 500) |
| Intervention | AI-driven analysis of intraoral mobile photographs for lesion detection | AI (CNN) analysis of intraoral photographs (n=6) |
| Comparison | Conventional diagnostic standards (e.g., histopathology) | Histopathology or conventional reference standard (n=6) |
| Outcomes | Diagnostic performance metrics: sensitivity, specificity, accuracy; applicability | Sensitivity (n=6); specificity (n=5) |
| Study designs | Systematic reviews/meta-analyses (umbrella review); cross-sectional study designs; English only | Systematic reviews with meta-analysis (n=6) |
| Timing | Not specified | Not specified |