“Enhancing early detection of oral cancer: a comparative study of artificial intelligence models and clinical specialist in lesion classification”
Shima Soleimani Sardou, Mohammad Mehdi Ghaemi, Fatemeh Sadat Rezvaninejad, Abolfazl Seyrfar, Arash Shahravan, Nader Navabi, Raziyehsadat Rezvaninejad · 2025
Read “Enhancing early detection of oral cancer: a comparative study of artificial intelligence models and clinical specialist in lesion classification” by Shima Soleimani Sardou, Mohammad Mehdi Ghaemi, Fatemeh Sadat Rezvaninejad, Abolfazl Seyrfar, Arash Shahravan, Nader Navabi, Raziyehsadat Rezvaninejad (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12821243.txt.
Description
Shima Soleimani Sardou and co-authors compare in 2025 how well AI models and a human specialist sort mouth lesions from photos, aiming at earlier oral cancer detection. The cancer is a global burden, and its varied look makes early spotting hard. Photos taken inside the mouth offer a cheap screening route.
The data set held 518 clinic images gathered over 2009 to 2023 at a dental faculty in Kerman. Of these, 104 showed malignant lesions and 414 benign or normal tissue, all confirmed by a pathology specialist. Three pretrained deep networks were tested on the set. A model that matches the specialist could triage photos in clinics with no specialist nearby. The authors report how close each model came.
Catalog record
| CREATOR | Shima Soleimani Sardou, Mohammad Mehdi Ghaemi, Fatemeh Sadat Rezvaninejad, Abolfazl Seyrfar, Arash Shahravan, Nader Navabi, Raziyehsadat Rezvaninejad |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 29 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |