Breast tumor detection and classification on the Internet of Medical Things (IoMT) can be
automated with the potential of Artificial Intelligence (AI). Deep learning models rely on large …

A crucial element in the diagnosis of breast cancer is the utilization of a classification method
that is efficient, lightweight, and precise. Convolutional neural networks (CNNs) have …

Pathologists use biopsies and microscopic examination to accurately diagnose breast
cancer. This process is time-consuming, labor-intensive, and costly. Convolutional neural …

Lung cancer is recognized as the most life-threatening cancer among other type of cancers
all over the world. Early stage recognition and proper diagnosis can increase the five-year …

Simple Summary Breast cancer is one of the leading causes of cancer death among women.
Developing machine learning-based diagnosis models receives great attention from …

Throughout history until today, hepatocellular carcinoma (HCC) remains one of the most
serious illnesses worldwide due to its high mortality rates. One of the most essential steps to …

Abstract Medical Imaging with Deep Learning has recently become the most prominent topic
in the scientific world. Significant results have been obtained in the classification of medical …

Objective. Learning-based histopathology image (HI) classification methods serve as
important tools for auxiliary diagnosis in the prognosis stage. However, most existing …

The variable magnification levels in histopathology images make it difficult to accurately
categorize tumor regions in breast cancer histology. In this study, a novel architecture for …

Difficulties associated with identifying lymph nodes metastasis in esophageal squamous cell
carcinoma (ESCC LNM) can make it challenging to determine the clinical stage and devize …