ARTIFICIAL INTELLIGENCE IN RADIOLOGY: SYSTEMATIC REVIEW

Introduction: Radiology, integral to modern medicine since the discovery of X-rays, has evolved to integrate AI and machine learning, reshaping healthcare. This review explores their impact on radiology, aiming to guide discussions among clinicians, researchers, and policymakers for improved patient outcomes and future directions in AI-driven radiology.

Methods: The researchers in this study followed the 2020 Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines to ensure that their work met the required standards. This was done to ensure the precision and reliability of the conclusions derived from the research.

Result: Our search produced 17 results. After looking at the titles and summaries, we discovered 10 papers that fit our criteria after excluding several articles because they did not fit into criteria. But after reading the full papers carefully, we included five papers in our final analysis. These papers included a retrospective observational study and several case reports.

Conclusion: Overall, these studies and trials illustrate the promising potential of AI in healthcare, particularly in radiology, while underscoring the need for continued research, larger-scale studies, and addressing limitations to harness its full benefits and ensure patient-centered, effective, and ethical integration into medical practices.