Acute Lymphoblastic Leukemia Diagnosis Employing Deep Learning Models

This project utilizes image preprocessing and advanced deep learning models, namely, YOLOv8, YOLOv11, ResNet50 and Inception-ResNet-v2 for Acute Lymphoblastic Leukemia Diagnosis; the study achieves accuracy rates as high as 99.7%, demonstrating the effectiveness of these algorithms across multiple datasets and various real-world situations.