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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM30082
Volume:
8 |
4 |
Apr 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This paper proposes an automatic system for detecting WBC cancers like AML, ALL, CLL, and CML, integrating image processing techniques. By automating analysis through advanced algorithms, it eliminates operator variability, ensuring consistent and objective results. Machine learning models classify cells for high accuracy, and seamless healthcare integration. This approach promises to enhance diagnostic efficiency and reliability in WBC cancer detection.
KEYWORDS
Publication Date
12/31/45385
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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