Enhancing malignant transformation predictions in oral potentially malignant disorders: A novel machine learning framework using real-world data

Enhancing malignant transformation predictions in oral potentially malignant disorders: A novel machine learning framework using real-world data

Summary: This study addresses the challenge of accurately predicting malignant transformation risk in patients with oral potentially malignant disorders (OPMDs). Using data from 1,094 patients across three institutions (2004–2023), the researchers compared traditional statistical methods, including...

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Bibliographic Details
Main Authors: Jing Wen Li, Meng Jing Zhang, Ya Fang Zhou, John Adeoye, Jing Ya Jane Pu, Peter Thomson, Colman Patrick McGrath, Dian Zhang, Li Wu Zheng
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:iScience
Subjects:
Public health
Artificial intelligence
Online Access:http://www.sciencedirect.com/science/article/pii/S2589004225003220
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