Research into the potential benefits of artificial intelligence for comprehending the intricate
biology of cancer has grown as a result of the widespread use of deep learning and …

Cancer remains a formidable global health challenge, claiming millions of lives annually.
Timely and accurate cancer diagnosis is imperative. While numerous reviews have explored …

Colorectal cancer (CRC) exhibits a significant death rate that consistently impacts human
lives worldwide. Histopathological examination is the standard method for CRC diagnosis …

Introduction Deep learning-based solutions for histological image classification have gained
attention in recent years due to their potential for objective evaluation of histological images …

Accurate cancer detection and diagnosis are imperative for advancing patient outcomes and
mitigating mortality rates. This extensive review scrutinizes the progress within the domain of …

The fat mass and obesity-associated (FTO) protein catalyzes metal-dependent modifications
of nucleic acids, namely the demethylation of methyl adenosine inside mRNA molecules …

Ovarian carcinoma is known for its diverse subtypes with unique morphologies and clinical
characteristics, causing considerable diagnostic complexities. While deep learning has …

Aim: Therefore, this study aims to develop a robust and efficient classification system for
colorectal cancer through Convolutional Neural Networks (CNNs) on histological images …

Objectives: The objective of this work is to obtain an efficient medical image retrieval and
classification from a larger healthcare datasets using Novel approach. Methods: In this study …

Globally, Colorectal Cancer (CRC) is the one most significant cancer types as well as it
grows in a region of colon of large intestine. An early CRC detection is supportive to handle …