Journal of Cancer Research and Immuno-Oncology
Open Access

Abstract

A Comprehensive Review of Deep Learning and Artificial Intelligence in Cancer Diagnosis

Deepa Rangasamy*

The application of Artificial Intelligence (AI) in cancer detection has shown promising potential to improve diagnostic accuracy and patient outcomes. This review aims to provide a comprehensive overview of the current state of AI in cancer detection and its implications in clinical practice. We systematically reviewed the literature to identify relevant studies on AI-based cancer detection. The review covers various cancer types, including breast, lung, skin, and others. We examined the AI algorithms used, such as machine learning and deep learning, and the diagnostic modalities employed, such as medical imaging and pathology. Performance metrics, including sensitivity, specificity, and accuracy, were assessed to evaluate the effectiveness of AI algorithms in cancer detection. The key findings demonstrate that AI algorithms can achieve comparable or even superior performance to human experts in detecting and classifying cancer. However, challenges such as data quality, interpretability, and algorithm robustness need to be addressed for successful implementation.

Published Date: 2024-12-27; Received Date: 2023-07-25