Machine Learning Algorithms Based Approach for Detecting the LeukemiaDisease

Detecting leukemia, a condition characterized by significantly elevated blood cell counts compared to healthy individuals, typically relies on repeated full blood counts due to the challenge posed by malignant cells resembling normal blood cells. Early identification and treatment are crucial to prevent complications. Current laboratory procedures for leukemia detections are time wasting. Following study proposes a machine learning approach of leukemia detection. The dataset comprising images of lifeblood smears is aggregated and processed to extract wanted features. These are utilized to fit and examine unlike methods, including KNearest Neighbour, Decision Tree, Random Forest, and Logistic Regression. Comparison of classifiers' performance against multiple criteria, such as accuracy and precision, aids in identifying the most effective classifier.