Understanding Artificial Intelligence-Based Approaches for Enhancing Cancer Diagnosis Through Medical Imaging

Abstract

Artificial Intelligence (AI) transforms healthcare by using its power to improve medical imaging diagnostic accuracy along with increased efficiency and effectiveness in cancer detection. Medical imaging systems now integrate AI-based techniques notably machine learning (ML) together with deep learning (DL) to automatize the interpretation of radiological images which include CT scans and X-rays and MRI and histopathological slides. This research examines Artificial Intelligence systems in medical imaging with special emphasis on applications related to cancer diagnosis. Academic language: The deployment of machine learning algorithms enhances image diagnostics leading to better early cancer identification which results in enhanced patient treatment outcomes. An examination of medical imaging techniques through convolutional neural networks (CNNs), reinforcement learning, and hybrid models represents the main focus of this review. This discourse explains both the obstacles facing the adoption of AI in clinical environments alongside potential opportunities that AI creates for therapeutic detection.