 Acute lymphoblastic leukemia, all, is a form of cancer that affects the white blood cells in the bone marrow. It is one of the most common cancers in children and adults, and it is often difficult to detect because of the similarities between healthy and diseased cells at the beginning of the disease. Computer-aided systems are being used to help pathologists identify the disease quickly and accurately. These systems use image processing techniques to improve the quality of the images and extract relevant information from them. Then, they feed the data into machine learning algorithms like convolutional neural networks, CNNs, which are able to recognize patterns and distinguish between healthy and unhealthy cells. Finally, the results are combined with other data sources to provide accurate diagnoses. This article was authored by Ibrahim Abdul Rabb Ahmed, Ibrahim Mohamed Senan, Hamza Salameh Ahmad Shatniwi and others.