Deep Learning Facilitates Distinguishing Histologic Subtypes of Pulmonary Neuroendocrine Tumors on Digital Whole-Slide Images

SIMPLE SUMMARY: Challenges persist in diagnosing pulmonary neuroendocrine tumors. Our case study shows that deep learning combined with convolutional neural networks has the potential to assist in the diagnosis of pulmonary neuroendocrine tumors from digital whole-slide images. ABSTRACT: The histolo...

Descripción completa

Detalles Bibliográficos
Autores principales: Ilié, Marius, Benzaquen, Jonathan, Tourniaire, Paul, Heeke, Simon, Ayache, Nicholas, Delingette, Hervé, Long-Mira, Elodie, Lassalle, Sandra, Hamila, Marame, Fayada, Julien, Otto, Josiane, Cohen, Charlotte, Gomez-Caro, Abel, Berthet, Jean-Philippe, Marquette, Charles-Hugo, Hofman, Véronique, Bontoux, Christophe, Hofman, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8996915/
https://www.ncbi.nlm.nih.gov/pubmed/35406511
http://dx.doi.org/10.3390/cancers14071740

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8996915/
https://www.ncbi.nlm.nih.gov/pubmed/35406511
http://dx.doi.org/10.3390/cancers14071740

Ejemplares similares