Predicting Leukoplakia and Oral Squamous Cell Carcinoma Using Interpretable Machine Learning: A Retr...
Predicting Leukoplakia and Oral Squamous Cell Carcinoma Using Interpretable Machine Learning: A Retrospective Analysis
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Palermo: MDPI AG
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Language
English
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Palermo: MDPI AG
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Purpose: The purpose of this study is to assess the effectiveness of the best performing interpretable machine learning models in the diagnoses of leukoplakia and oral squamous cell carcinoma (OSCC). Methods: A total of 237 patient cases were analysed that included information about patient demographics, lesion characteristics, and lifestyle factor...
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Predicting Leukoplakia and Oral Squamous Cell Carcinoma Using Interpretable Machine Learning: A Retrospective Analysis
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TN_cdi_doaj_primary_oai_doaj_org_article_89c2a64b47bf4226a0f94550d3ca5a7b
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_89c2a64b47bf4226a0f94550d3ca5a7b
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ISSN
2673-6373
E-ISSN
2673-6373
DOI
10.3390/oral4030032
