A deep hybrid learning pipeline for accurate diagnosis of ovarian cancer based on nuclear morphology

Nuclear morphological features are potent determining factors for clinical diagnostic approaches adopted by pathologists to analyze the malignant potential of cancer cells. Considering the structural alteration of the nucleus in cancer cells, various groups have developed machine learning techniques...

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Detalles Bibliográficos
Autores principales: Sengupta, Duhita, Ali, Sk Nishan, Bhattacharya, Aditya, Mustafi, Joy, Mukhopadhyay, Asima, Sengupta, Kaushik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8741040/
https://www.ncbi.nlm.nih.gov/pubmed/34995293
http://dx.doi.org/10.1371/journal.pone.0261181

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8741040/
https://www.ncbi.nlm.nih.gov/pubmed/34995293
http://dx.doi.org/10.1371/journal.pone.0261181

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