Year: 2024
Type: article
Abstract: Artificial Intelligence (AI) has rapidly gained widespread attention and has made unprecedented strides in recent years, significantly influencing various sectors, especially the medical field. Its applications have revolutionized healthcare by assisting doctors in making faster, more accurate, and data-driven decisions. This paper aims to provide an in-depth analysis of AI's role in medical imaging, focusing on its applications in interpreting X-rays, CT scans, and MRIs. These imaging techniques utilize cutting-edge image recognition algorithms, with Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNNs) being the most prominent. AI not only improves diagnostic precision but also reduces human error, leading to better patient outcomes. Furthermore, the paper discusses current trends in AI-driven medical imaging and explores potential future directions, emphasizing how AI could continue to advance medical diagnostics and treatment planning, paving the way for more personalized and effective healthcare solutions.
DOI: 10.54097/rf9fh276
Author: Jialin Song
Institution: Capital Medical University
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4405809136