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- W4308752105 abstract "Leukaemia is one of the blood malignancies because of the strange expansion of white platelets in the bone marrow of the human body. A haematologist utilises microscopic investigation of the human blood, which encourages the need for techniques that are infinitesimal image shading, division, arrangement, and bunching, which permits the identification of a patient's experience with leukaemia. The manual infinitesimal assessment of bone marrow is less precise, tedious, and vulnerable to mistakes, which causes it to be hard for laboratory labourers to precisely perceive the qualities of impact cells. The additionally contrasted informational indexes and diverse shading models allow you to look at the presentation's changed shading pictures. Experts and professionals who work with stained photographs of leukaemia patients will benefit from this method's discovery of a crucial component. Algorithms for detecting leukaemia have been studied in this research. The methodology and efficiency are compared, which can be used for different analyses by the researchers." @default.
- W4308752105 created "2022-11-15" @default.
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- W4308752105 date "2022-11-10" @default.
- W4308752105 modified "2023-09-27" @default.
- W4308752105 title "A Survey on Machine Learning-Based Approaches for Leukaemia Detection" @default.
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- W4308752105 doi "https://doi.org/10.1007/978-981-19-5090-2_5" @default.
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