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Study of morphological and textural features for classification of oral squamous cell carcinoma by traditional machine learning techniques
BACKGROUND: Oral squamous cell carcinoma (OSCC) is the most prevalent form of oral cancer. Very few researches have been carried out for the automatic diagnosis of OSCC using artificial intelligence techniques. Though biopsy is the ultimate test for cancer diagnosis, analyzing a biopsy report is a v...
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| Pubblicato in: | Cancer Rep (Hoboken) |
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| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
John Wiley and Sons Inc.
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7941561/ https://ncbi.nlm.nih.gov/pubmed/33026718 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/cnr2.1293 |
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