Classifying microscopic images as acute lymphoblastic leukemia by Resnet ensemble model and Taguchi method

Classifying microscopic images as acute lymphoblastic leukemia by Resnet ensemble model and Taguchi method

Background: Researchers have attempted to apply deep learning methods of artificial intelligence for rapidly and accurately detecting acute lymphoblastic leukemia (ALL) in microscopic images. Results: A Resnet101-9 ensemble model was developed for classifying ALL in microscopic images. The proposed...

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Bibliographic Details
Main Authors: Chen, Y.-M (Author), Chou, F.-I (Author), Ho, W.-H (Author), Tsai, J.-T (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
Acute lymphoblastic leukaemias
Acute lymphoblastic leukemia
Algorithm hyperparameter
Deep learning
Diseases
ensemble model
Ensemble models
Hyper-parameter
Image classification
Individual modeling
Learning algorithms
Microscopic image
Model method
Resnet model
Statistical tests
Taguchi experimental method
Taguchi methods
Taguchi's methods
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