Brief Report
Version 1
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A Step Toward the Future: Using Machine Learning to Detect Leukemia.
Version 1
: Received: 17 July 2023 / Approved: 17 July 2023 / Online: 17 July 2023 (11:32:55 CEST)
How to cite: Magotra, N. A Step Toward the Future: Using Machine Learning to Detect Leukemia.. Preprints 2023, 2023071114. https://doi.org/10.20944/preprints202307.1114.v1 Magotra, N. A Step Toward the Future: Using Machine Learning to Detect Leukemia.. Preprints 2023, 2023071114. https://doi.org/10.20944/preprints202307.1114.v1
Abstract
Leukemia is a cancer of the bone marrow, a spongy tissue that secretes into the bones and serves as the site for the production of blood cells. One of the most prevalent kinds of leukemia in adults is acute myeloid leukemia (AML). Leukemia has non-specific signs and symptoms that are also similar to those of other interpersonal illnesses. The only way to accurately diagnose leukemia is by manually examining a stained blood smear or bone marrow aspirate under the microscope. However, this approach takes more time and is less precise. This paper describes a method for the automatic recognition and classification of AML in blood smears. Classification techniques include decision trees, logistic regression, support vector machines, and naive bayes.
Keywords
automatic leukemia detection, acute lymphoblastic leukemia, lymphocyte image segmentation, machine learning
Subject
Computer Science and Mathematics, Other
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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