Unknown

Dataset Information

Artificial intelligence for cellular phenotyping diagnosis of nasal polyps by whole-slide imaging.


ABSTRACT:

Background

artificial intelligence (AI) for cellular phenotyping diagnosis of nasal polyps by whole-slide imaging (WSI) is lacking. We aim to establish an AI chronic rhinosinusitis evaluation platform 2.0 (AICEP 2.0) to obtain the proportion of inflammatory cells for cellular phenotyping diagnosis of nasal polyps and to explore the clinical significance of different phenotypes of nasal polyps on the WSI.

Methods

a total of 453 patients were enrolled in our study. For the development of AICEP 2.0, 179 patients (WSIs) were obtained from the Third Affiliated Hospital of Sun Yat-Sen University (3HSYSU) from January 2008 to December 2018. A total of 24,625 patches were automatically extracted from the regions of interest under a 400× HPF by Openslide and the number of inflammator

SUBMITTER: Wu Q 

PROVIDER: S-EPMC8050855 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

altmetric image

Publications

Sorry, this publication's infomation has not been loaded in the Indexer, please go directly to PUBMED or Altmetric.

Similar Datasets