Development and Evaluation of a Convolutional Neural Network for Microscopic Diagnosis Between Pleomorphic Adenoma and Carcinoma Ex‐Pleomorphic Adenoma

The study underscores the potential of ResNet-50 in the microscopic diagnosis of carcinoma ex-pleomorphic adenoma. The developed model demonstrated strong learning potential, but exhibited partial limitations in generalization, as indicated by the validation curve. In summary, the study established a promising baseline despite limitations in model generalization. This indicates the need to refine methodologies, investigate new models, incorporate larger datasets, and encourage inter-institutional collaboration for comprehensive studies in salivary gland tumors.

Authors

Institutions

Publication Details

Journal
Head & Neck
Published
2024-10-27
DOI
https://doi.org/10.1002/hed.27971
Citations
4
Primary Topic
Salivary Gland Tumors Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
2.29

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development and Evaluation of a Convolutional Neural Network for Microscopic Diagnosis Between Pleomorphic Adenoma and Carcinoma Ex‐Pleomorphic Adenoma

Amanda de Farias Gabriel, Takefumi Nakamura, Márcio Ajudarte Lopes, Sebastião Silvério Sousa‐Neto et al.
4 citations
Head & Neck
Salivary Gland Tumors Diagnosis and Treatment
2.29
article

Development and Evaluation of a Convolutional Neural Network for Microscopic Diagnosis Between Pleomorphic Adenoma and Carcinoma Ex‐Pleomorphic Adenoma

Amanda de Farias Gabriel, Takefumi Nakamura, Márcio Ajudarte Lopes, Sebastião Silvério Sousa‐Neto, Virgílio Gonzales Zanella, Alan Roger Santos‐Silva, Manoela Domingues Martins, Anna Luíza Damaceno Araújo, Ana Lúcia Carrinho Ayroza Rangel, Daniela Giraldo‐Roldán, Luiz Paulo Kowalski, Marco Antônio Trevizani Martins, Matheus Cardoso Moraes, Felipe Paiva Fonseca, Cínthia Verónica Bardález López de Cáceres, Pablo Agustín Vargas, Giovanna Calabrese dos Santos
article en
4 citations

Abstract

The study underscores the potential of ResNet-50 in the microscopic diagnosis of carcinoma ex-pleomorphic adenoma. The developed model demonstrated strong learning potential, but exhibited partial limitations in generalization, as indicated by the validation curve. In summary, the study established a promising baseline despite limitations in model generalization. This indicates the need to refine methodologies, investigate new models, incorporate larger datasets, and encourage inter-institutional collaboration for comprehensive studies in salivary gland tumors.

Head & NeckVol. 47(3)
Universidade Federal de Minas Gerais (BR), Universidade Federal do Rio Grande do Sul (BR), Universidade Federal de Ciências da Saúde de Porto Alegre (BR), Universidade de São Paulo (BR), Universidade Estadual de Campinas (UNICAMP) (BR), Universidade Estadual do Oeste do Paraná (BR), AC Camargo Hospital (BR), Universidade Federal de São Paulo (BR)
Fundação de Amparo à Pesquisa do Estado de São Paulo, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa do Estado de Minas Gerais, Ministério da Saúde, Fundo de Apoio ao Ensino, à Pesquisa e Extensão, Universidade Estadual de Campinas
Partnerships for the goals
Openalex Percentile: Top 11%
Salivary Gland Tumors Diagnosis and Treatment
2.29
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.