Classification of Blood Cell Data using Deep Learning Approach
Sravya Yepuri, Ashapurna Marandi · 2023
Machine Learning is an established branch of artificial intelligence that comprises of algorithms and mathematical relationships and is rapidly being used to clinical research. Machine Learning enables computers to be programmed without explicit information and to learn from it. The outcomes of using these technologies in medical data processing have been amazing, with great effectiveness in detecting illnesses. According to studies, Machine Learning techniques significantly improve complex medical decision-making processes in medical image processing by extracting and then evaluating the features of these pictures. An urgent demand for more sophisticated data analysis approaches has arisen as the number of medical diagnosis tools rose and a significant amount of high-quality data was produced. Traditional methodologies are incapable of examining such vast amounts of data. One of the critical diseases, Leukemia can be found in the blood cell data image of patients by applying machine learning algorithms. Here in this paper, the blood cell images available in the open literature are analyzed using the different algorithm networks for the refinement of images to identify the diseases like leukemia.