Machine learning concepts applied to oral pathology and oral medicine: A convolutional neural networks' approach

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Damaceno Araujo, Anna Luiza ; da Silva, Viviane Mariano ; Kudo, Maira Suzuka ; Carlos de Souza, Eduardo Santos ; Saldivia-Siracusa, Cristina ; Giraldo-Roldan, Daniela ; Lopes, Marcio Ajudarte ; Vargas, Pablo Agustin ; Khurram, Syed Ali ; Pearson, Alexander T. ; Kowalski, Luiz Paulo ; de Leon Ferreira de Carvalho, Andre Carlos Ponce ; Santos-Silva, Alan Roger ; Moraes, Matheus Cardoso

• Tipo de documento: Artigo Científico
• Fonte: JOURNAL OF ORAL PATHOLOGY & MEDICINE; v. 52, n. 2, p. 10-pg., 2023-01-04.

Resumo

IntroductionArtificial intelligence models and networks can learn and process dense information in a short time, leading to an efficient, objective, and accurate clinical and histopathological analysis, which can be useful to improve treatment modalities and prognostic outcomes. This paper targets oral pathologists, oral medicinists, and head and neck surgeons to provide them with a theoretical and conceptual foundation of artificial intelligence-based diagnostic approaches, with a special focus on convolutional neural networks, the state-of-the-art in artificial intelligence and deep learning. MethodsThe authors conducted a literature review, and the convolutional neural network's conceptual foundations and functionality were illustrated based on a unique interdisciplinary point of view. ConclusionThe development of artificial intelligence-based models and computer vision methods for pattern recognition in clinical and histopathological image analysis of head and neck cancer has the potential to aid diagnosis and prognostic prediction. (AU)

• Processo FAPESP: 09/53839-2 - Criação do Laboratório de Patologia Digital através do uso do escaneador de lâminas histológicas (Aperio® Scanscope CS)
• Beneficiário: Oslei Paes de Almeida
• Modalidade de apoio: Auxílio à Pesquisa - Programa Equipamentos Multiusuários
• Processo FAPESP: 21/14585-7 - Inteligência artificial aplicada ao diagnóstico clínico e histopatológico do Câncer de Cabeça e Pescoço
• Beneficiário: Anna Luiza Damaceno Araujo
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado