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About Review of Machine Learning Applications and Datasets in Classification of Acute Leukemia
The document reviews machine learning applications and datasets used to classify acute leukemia. It discusses literature on ML models for classifying acute lymphoid leukemia using blood smear images, with a focus on deep learning and traditional classifiers like support vector machines. The literature achieved accuracy ranging from the high 80s to high 90s percent for classification tasks.
Detailed Information
Author: | ['Lewis Torres'] |
---|---|
Publication Year: | 2021 |
Pages: | 9 |
Language: | English |
Format: | |
Price: | FREE |
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