Work

Machine Learning for Predicting Malignant Transformation in Actinic Cheilitis: A Prognostic Support System Based on Demographic and Clinical Descriptors

Year: 2026

Type: article

Study design: Observational Study

Source: Journal of Oral Pathology and Medicine

DOI: 10.1111/jop.70113

Authors: Ivan José Correia‐Neto, Alex Franco da Costa, Anna Luíza Damaceno Araújo, Cristina Saldivia‐Siracusa, Raísa Sales de Sá, Thiago Martini Pereira, Pablo Agustin Vargas, Alan Roger Santos‐Silva, Luiz Paulo Kowalski, Matheus Cardoso Moraes, Marcio Ajudarte Lopes

Institutions: Universidade Estadual de Campinas (UNICAMP), Universidade Federal de São Paulo, Universidade de São Paulo, Hospital Israelita Albert Einstein, Universidade Ceuma

Language: English

Topic: Oral Health Pathology and Treatment

Subfield: Periodontics

Field: Dentistry

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

Funder: Fundação de Amparo à Pesquisa do Estado de São Paulo

Awards: G5819034687, G7127764454, Creation of a Digital Pathology Laboratory using a histological slidescanner

OpenAlex ID: W7124910216

FWCI: 11.83

Cites: 25

Cited by: 2

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