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Review
. 2020;61(5):564-569.
doi: 10.11406/rinketsu.61.564.

[Artificial intelligence (AI) and hematological diseases: establishment of a peripheral blood convolutional neural network (CNN)-based digital morphology analysis system]

[Article in Japanese]
Affiliations
Review

[Artificial intelligence (AI) and hematological diseases: establishment of a peripheral blood convolutional neural network (CNN)-based digital morphology analysis system]

[Article in Japanese]
Akimichi Ohsaka. Rinsho Ketsueki. 2020.

Abstract

Morphological analysis of the blood smear is an essential element of diagnosing a disease hematologically and has been performed by conventional manual light microscopy for several decades. Although this method is the gold standard, it is labor-intensive, requires continuous training of the personnel, and is subject to relatively large interobserver variability. The artificial intelligence (AI)-based automated methods for the digital morphological analysis of blood smears have recently been developed. In this review, our recently developed convolutional neural network (CNN)-based digital morphology hematology analysis system is introduced. AI-based digital morphology hematology analysis system is firstly needed to incorporate digital imaging of blood cells into the analysis system. It is essential to establish a digital platform, which was already established in the radiological diagnosis, for the dissemination of CNN-based automated digital morphology hematology analyzer in the near future.

Keywords: Artificial intelligence; Convolutional neural networks; Digital imaging; Digital morphology hematology analyzer.

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