Paper Contents
Abstract
Deep learning has revolutionized the field of medical image analysis, offering unprecedented accuracy and efficiency in detecting and diagnosing cancer. This review focuses on state-of-the-art research in deep learning-based cancer detection published in 2024, covering various imaging modalities such as radiology, histopathology, and molecular imaging. The literature is analyzed to highlight the significant advancements, applications, and challenges in using deep learning for cancer detection. The paper provides a structured overview of 20 studies, emphasizing their conclusions, methodologies, and implications for future research
Copyright
Copyright © 2024 Er. Akashdeep Singh Rana, Er. Hitakshi. This is an open access article distributed under the Creative Commons Attribution License.
