In contemporary healthcare, medical image categorization is essential for illness prediction,
diagnosis, and therapy planning. The emergence of digital imaging technology has led to a …

Medical image classification, a critical component in medical diagnostics, has significantly
advanced through the integration of machine learning (ML) and deep learning (DL) …

Integrating medical imaging with computing technologies, such as Artificial Intelligence (AI)
and its subsets: Machine learning (ML) and Deep Learning (DL) has advanced into an …

Medical image classification plays a pivotal role in modern healthcare, aiding in accurate
disease diagnosis, treatment planning, and patient management. With the advent of deep …

Medical imaging is an indispensable component of modern healthcare, playing a critical role
in diagnosis, staging, and the assessment of treatment response for most major medical …

In the domain of modern deep learning and classification techniques, the convolutional
neural network (CNN) stands out as a highly successful and preferred method for image …

Deep Learning has become a well-known research field over the last several years. It is a
kind of Machine Learning, which is an offshoot of Artificial Intelligence. It can possibly rebuild …

AUCMEDI is a Python-based framework for medical image classification. In this paper, we
evaluate the capabilities of AUCMEDI, by applying it to multiple datasets. Datasets were …

Digital image processing has several uses, including machine vision, augmented reality,
and picture analysis. One such application is image segmentation. The segmentation of …

There is no doubt that medical imaging has become indispensable in disease diagnosis and
therapy. With advances in medical imaging, new imaging modalities and methodologies …