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Leukaemia is a disease that is related to cancerous cells. It is also lethal, and people of all age groups can be affected by it. WBCs especially affect this, and they are followed by a growth in the amount of lymphocytes that are still not mature and they can affect the blood or bone marrow. Hence, it is mandatory that periodic and proper cancer diagnosis should be carried out so that it can be detected at an early stage. At present, the process of detecting this deadly disease is manual. The blood samples collected using microscopic pictures which is highly sluggish and consumes a lot of time. Hence, an attempt has been done to use a new machine learning algorithm using a statistical segmentation. The proposed model can be utilized to create a suitable computer-aided diagnosis for leukaemia malignancy.

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Morphology-Based Machine Learning Mechanism for Unsupervised Framework Prediction Using Statistical Segmentation on Blood Cancer

  • 会议论文

  • 发表日期：

    2025年

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  • Moravani Poojaben Ishavarbhai,
  • Ajay Kumar Sharma,
  • Mayank Patel,
  • Narendra Singh Rathore

摘要

Leukaemia is a disease that is related to cancerous cells. It is also lethal, and people of all age groups can be affected by it. WBCs especially affect this, and they are followed by a growth in the amount of lymphocytes that are still not mature and they can affect the blood or bone marrow. Hence, it is mandatory that periodic and proper cancer diagnosis should be carried out so that it can be detected at an early stage. At present, the process of detecting this deadly disease is manual. The blood samples collected using microscopic pictures which is highly sluggish and consumes a lot of time. Hence, an attempt has been done to use a new machine learning algorithm using a statistical segmentation. The proposed model can be utilized to create a suitable computer-aided diagnosis for leukaemia malignancy.