Artificial Intelligence for Image Analysis in Oral Squamous Cell Carcinoma: A Review

被引：10

作者：

Pereira-Prado, Vanesa ^{[1
]}

Martins-Silveira, Felipe ^{[1
]}

Sicco, Estafania ^{[1
]}

Hochmann, Jimena ^{[1
]}

Isiordia-Espinoza, Mario Alberto ^{[2
]}

Gonzalez, Rogelio Gonzalez ^{[3
]}

Pandiar, Deepak ^{[4
]}

Bologna-Molina, Ronell ^{[1
,3
]}

机构：

[1] Univ Republica, Sch Dent, Mol Pathol Area, Montevideo 11400, Uruguay

[2] Univ Guadalajara, Inst Res Med Sci, Los Altos Univ Ctr, Dept Clin, Guadalajara 44100, Mexico

[3] Univ Juarez Estado Durango, Sch Dent, Res Dept, Durango 34000, Mexico

[4] Saveetha Dent Coll & Hosp, Dept Oral Pathol & Microbiol, Chennai 600077, India

来源：

DIAGNOSTICS | 2023年 / 13卷 / 14期

关键词：

artificial intelligence; deep learning; digital image; histopathological analysis; machine learning; oral squamous cell carcinoma; SEGMENTATION; DIAGNOSIS;

D O I：

10.3390/diagnostics13142416

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

Head and neck tumor differential diagnosis and prognosis have always been a challenge for oral pathologists due to their similarities and complexity. Artificial intelligence novel applications can function as an auxiliary tool for the objective interpretation of histomorphological digital slides. In this review, we present digital histopathological image analysis applications in oral squamous cell carcinoma. A literature search was performed in PubMed MEDLINE with the following keywords: "artificial intelligence" OR "deep learning" OR "machine learning" AND "oral squamous cell carcinoma". Artificial intelligence has proven to be a helpful tool in histopathological image analysis of tumors and other lesions, even though it is necessary to continue researching in this area, mainly for clinical validation.

引用

页数：13

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