Application of DL/ML in Diagnosis in Medical Imaging

Abstract

Disease diagnosis is a critical component of medical imaging in today's society. Medical imaging is commonly referred to as process and referred to as the process and practice of creating visual representations of a body's interior, which is employed in clinical evaluation and for training and medical simulation. Medical imaging uses x-rays and scans to examine the disease, too. Artificial intelligence and radiology offer better-than-human vision for medical imaging purposes. Machine learning (ML) is an application of artificial intelligence (AI) in which a system can be constructed and improved without requiring constant human intervention. In developing computer applications that can access and manipulate data, it focuses on data development. Machine learning approaches are increasingly utilized in diagnosis, prognosis, and risk assessment to use images. This chapter highlights new rules for imaging research and the results of which four issues that affect machine learning are discussed, including standardization of imagery protocols, diagnosing pathology changes, acquiring insight into images, and finally grasping the significance of test results.