GMM based deep convolutional neural network for Leukemia diagnosis

Leukaemia, a complex and heterogeneous group of blood cancer raises significant challenges in diagnosis due to its diverse subtypes and molecular characteristics. Recent advancements in genomic and molecular technologies have opened new avenues for improving diagnostic accuracy and personalized treatment strategies. This paper explores the journey towards enhancing the accuracy of Leukemia diagnosis, highlighting key innovations in genomic profiling, machine learning algorithms, and biomarker identification. By integrating these cutting-edge approaches, the paper demonstrates how precision medicine can revolutionize Leukaemia care, leading to better patient outcomes and a deeper understanding of the disease's underlying mechanisms. The findings underscore the importance of multidisciplinary collaboration and continuous research in the quest to combat Leukaemia more effectively.