AI in Healthcare: Transforming Diagnosis with Deep Learning in Medical Imaging

Abstract

This paper investigates the transformative impact of deep learning technologies on medical imaging diagnosis within the healthcare sector. We explore how deep learning algorithms, particularly convolutional neural networks (CNNs), have significantly improved the accuracy, speed, and consistency of detecting diseases such as cancer, neurological disorders, and cardiovascular conditions. The paper also addresses the practical challenges of deploying AI models in clinical environments, including data scarcity, model interpretability, and ethical considerations. Through case studies and recent advancements, we illustrate how deep learning is not only enhancing diagnostic capabilities but also shaping the future of personalized medicine. The findings suggest that integrating deep learning into medical imaging workflows holds great promise for improving patient outcomes and healthcare system efficiency.