Publication2024
Diagnostic performance of artificial intelligence in detecting oral potentially malignant disorders and oral cancer using medical diagnostic imaging: a systematic review and meta-analysis
The record
- Type
- Publication
- Date
- 1 January 2024
- Level
- National
- Journal
- Frontiers in Oral Health
- Volume
- 5
- Published
- 1 January 2024
- DOI
- 10.3389/froh.2024.1494867
- Scopus ID
- 85209538190
- ISSN
- 26734842
- Authors
- 7
- Open access
- Yes
- Citations
- 36
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
3.4 Reduce premature mortality from non-communicable diseases and promote mental health and well-being
Health outcome: AI algorithms demonstrate 87% sensitivity and 81% specificity for early diagnosis of oral potentially malignant disorders and oral cancer with high diagnostic odds ratio of 131.63
- Certain confidence
- The record states the subject matter explicitly. A reader shown only the title and this goal would agree without hesitation. Example: a workshop titled "Renewable Energy and Smart Grid" against SDG 7.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-1.2 Health and well-being
Early detection of oral cancer offers significant advantages in resource-constrained settings for improved survival outcomes
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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Provenance
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Diagnostic performance of artificial intelligence in detecting oral potentially malignant disorders and oral cancer using medical diagnostic imaging: a systematic review and meta-analysis”. Kortex.