Clinical trial · Interventional
Application and Validation of a Smartphone-based Deep Learning System for Oral Potentially Malignant Disorders and Oral Cancer Screening
Application and Validation of a Smartphone-based Deep Learning System for Oral Potentially Malignant Disorders (OPMD) and Oral Cancer Screening
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The goal of this clinical trial is to learn if smartphone-based deep learning system works to accurately detect oral potentially malignant disorders and oral cancer in adults. It will also learn about if it is as effective as assessments conducted by dentists and non-certified health provider. We expect that the deep learning system will have higher sensitivity in detecting oral potentially malignant disorders and oral cancer, where as the dentists and non-certified health providers will exhibit higher specificity in screening. Participants will be grouped into three arms: deep learning system (arm A) or board-certified dentist with deep learning system (arm B) or non-certified health providers (general practitioners) with deep learning system (arm C). Oral cancer risk factors, such as habits of smoking or having chewed betel nut or alcohol drinking, would be recorded by anonymous questionnaires.
Conditions
Conditions (3)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Cancer Screening | — | UNRESOLVED | — |
| Oral Cancer | Malignant Lip and Oral Cavity Neoplasm | CURATED_BROADER | 0.80 |
| Oral Potentially Malignant Disorders | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Smartphone-based deep learning system | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (3)
- type
- EXPERIMENTAL
- label
- A
- description
- Deep learning system
- interventionNames
- Device: Smartphone-based deep learning system
- type
- ACTIVE_COMPARATOR
- label
- B
- description
- Board-certified dentist with deep learning system
- interventionNames
- Device: Smartphone-based deep learning system
- type
- ACTIVE_COMPARATOR
- label
- C
- description
- non-certified health providers (general practitioners) with deep learning system
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 19 Years
Show eligibility criteria text
Inclusion Criteria: * Adult patients (age ≥18) visiting cancer screening center Exclusion Criteria: * Unable to cooperate to fully open mouth/ navigate tongue * Unable to cooperate for the assessment
References
Publications (11)
- BACKGROUNDHsu Y, Chou CY, Huang YC, Liu YC, Lin YL, Zhong ZP, Liao JK, Lee JC, Chen HY, Lee JJ, Chen SJ. Oral mucosal lesions triage via YOLOv7 models. J Formos Med Assoc. 2025 Jul;124(7):621-627. doi: 10.1016/j.jfma.2024.07.010. Epub 2024 Jul 12. PMID 39003230
- BACKGROUNDTanriver G, Soluk Tekkesin M, Ergen O. Automated Detection and Classification of Oral Lesions Using Deep Learning to Detect Oral Potentially Malignant Disorders. Cancers (Basel). 2021 Jun 2;13(11):2766. doi: 10.3390/cancers13112766. PMID 34199471
- BACKGROUNDHegde S, Ajila V, Zhu W, Zeng C. Artificial intelligence in early diagnosis and prevention of oral cancer. Asia Pac J Oncol Nurs. 2022 Aug 24;9(12):100133. doi: 10.1016/j.apjon.2022.100133. eCollection 2022 Dec. PMID 36389623
- BACKGROUNDNg SW, Syamim Syed Mohd Sobri SN, Zain RB, Kallarakkal TG, Amtha R, Wiranata Wong FA, Rimal J, Durward C, Chea C, Jayasinghe RD, Vatanasapt P, Saleha Binti Ibrahim Tamin N, Cheng LC, Mazlipah Binti Ismail S, Tepirou C, Ariff Bin Abdul Rahman Z, Rajendran S, Kanapathy J, Liew CS, Cheong SC. Barriers to early detection and management of oral cancer in the Asia Pacific region. J Health Serv Res Policy. 2022 Apr;27(2):133-140. doi: 10.1177/13558196211053110. Epub 2022 Jan 22. PMID 35068209
- BACKGROUNDKhanagar SB, Naik S, Al Kheraif AA, Vishwanathaiah S, Maganur PC, Alhazmi Y, Mushtaq S, Sarode SC, Sarode GS, Zanza A, Testarelli L, Patil S. Application and Performance of Artificial Intelligence Technology in Oral Cancer Diagnosis and Prediction of Prognosis: A Systematic Review. Diagnostics (Basel). 2021 May 31;11(6):1004. doi: 10.3390/diagnostics11061004. PMID 34072804
- BACKGROUNDGigliotti J, Madathil S, Makhoul N. Delays in oral cavity cancer. Int J Oral Maxillofac Surg. 2019 Sep;48(9):1131-1137. doi: 10.1016/j.ijom.2019.02.015. Epub 2019 Mar 13. PMID 30878273
- Peacock ZS, Pogrel MA, Schmidt BL. Exploring the reasons for delay in treatment of oral cancer. J Am Dent Assoc. 2008 Oct;139(10):1346-52. doi: 10.14219/jada.archive.2008.0046.