A deep learning diagnostic platform for diffuse large B-cell lymphoma with high accuracy across multiple hospitals.

ABSTRACT: Diagnostic histopathology is a gold standard for diagnosing hematopoietic malignancies. Pathologic diagnosis requires labor-intensive reading of a large number of tissue slides with high diagnostic accuracy equal or close to 100 percent to guide treatment options, but this requirement is difficult to meet. Although artificial intelligence (AI) helps to reduce the labor of reading pathologic slides, diagnostic accuracy has not reached a clinically usable level. Establishment of an AI model often demands big datasets and an ability to handle large variations in sample preparation and image collection. Here, we establish a highly accurate deep learning platform, consisting of multiple convolutional neural networks, to classify pathologic images by using smaller datasets. We analyze human diff

SUBMITTER: Li D 

PROVIDER: S-EPMC7691991 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature