AI Looks at Medical Images: How Machines Can Help Doctors Interpret Medical Images Like X-rays and MRIs

EasyChair Preprint 14837

Abstract

 AI Looks at Medical Images: How Machines Can Help Doctors Interpret Medical Images Like X-rays and MRIs

The integration of Artificial Intelligence (AI) into medical imaging has revolutionized the way doctors interpret complex diagnostic images, such as X-rays, MRIs, and CT scans. This paper explores how AI technologies, particularly machine learning and deep learning algorithms, are enhancing the accuracy, efficiency, and accessibility of medical image interpretation. AI excels in identifying patterns and detecting abnormalities, helping doctors diagnose conditions ranging from fractures to tumors with greater precision and speed. By augmenting human expertise, AI reduces errors caused by human fatigue and variability, while streamlining the review process in healthcare systems increasingly burdened by high volumes of imaging data. Despite its advantages, AI faces challenges, including data bias, ethical concerns, and regulatory barriers. As AI continues to evolve, its potential to complement medical professionals and improve patient outcomes is immense, but careful consideration must be given to its limitations and the need for responsible implementation.

Keyphrases: AI faces challenges, Artificial Intelligence, doctors interpret complex, including data bias

@booklet{EasyChair:14837,
  author    = {Docas Akinyele and Godwin Olaoye},
  title     = {AI Looks at Medical Images: How Machines Can Help  Doctors Interpret Medical Images Like X-rays and MRIs},
  howpublished = {EasyChair Preprint 14837},
  year      = {EasyChair, 2024}}