Oral Cancer Clinical Trial
Official title:
The Application of an Artificial Intelligence Based Program to Classify Oral Cavity Findings Based on Clinical Image Analysis
This study aims to develop an AI program that can classify oral findings into Normal/variation of normal or an oral disease by clinical photos analysis, aiding in lowering the percentages of false positive and false negative diagnosis of oral diseases.
Status | Not yet recruiting |
Enrollment | 241 |
Est. completion date | September 1, 2024 |
Est. primary completion date | August 1, 2024 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: - Patients above 18 years old - Candidates with normal oral cavity findings - Candidates with variations of oral cavity findings - Candidates with different oral lesions Exclusion Criteria: • Patients less than 18 years old |
Country | Name | City | State |
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n/a |
Lead Sponsor | Collaborator |
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Cairo University |
Khanagar SB, Al-Ehaideb A, Maganur PC, Vishwanathaiah S, Patil S, Baeshen HA, Sarode SC, Bhandi S. Developments, application, and performance of artificial intelligence in dentistry - A systematic review. J Dent Sci. 2021 Jan;16(1):508-522. doi: 10.1016/j.jds.2020.06.019. Epub 2020 Jun 30. — View Citation
Seoane Leston JM, Aguado Santos A, Varela-Centelles PI, Vazquez Garcia J, Romero MA, Pias Villamor L. Oral mucosa: variations from normalcy, part I. Cutis. 2002 Feb;69(2):131-4. — View Citation
Tanriver 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. — View Citation
Varela-Centelles P, Lopez-Cedrun JL, Fernandez-Sanroman J, Seoane-Romero JM, Santos de Melo N, Alvarez-Novoa P, Gomez I, Seoane J. Key points and time intervals for early diagnosis in symptomatic oral cancer: a systematic review. Int J Oral Maxillofac Surg. 2017 Jan;46(1):1-10. doi: 10.1016/j.ijom.2016.09.017. Epub 2016 Oct 15. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | risk stratification | patient is either normal with no risk or need for referral, low risk of malignant transformation disease, high risk of malignant transformation disease. | 3 months to develop the program |
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