Radiology Comprehensive Review of AI-Driven Imaging Technologies and their Impact on Diagnostic Accuracy
Radiology has also received the double-edged gift of artificial intelligence (AI) that accelerates the speed and efficiency of diagnosis. This systematic review aims to present the outcome of AI-assisted imaging, from accuracy examinations to advancing radiology work processes. It looks at different AIs using algorithms in imaging techniques like X-rays, CT scans, MRI, and ultrasounds. AI can benefit radiologists by enhancing results in detecting diseases, including cancers, cardiovascular diseases, and neurological disorders. Still, some barriers to adoption, data quality, and ethical issues have not been addressed. This review addresses these concerns while also considering how AI may enhance patient outcomes and radiology operations.
Authors
- H. Alshammari (ORCID: https://orcid.org/0000-0001-8443-4102)
- Khalid Alanazi (ORCID: https://orcid.org/0000-0002-5169-2524)
- Amal Alharbi (ORCID: https://orcid.org/0000-0001-7730-0720)
- Dalal Alshammari
- Ahmed Aiah Abdullah Alrashdi
- Afrah Manwer Eieed Alrasheedi
- Norah Fahhad G Alazmi
- Adel Abdullah Bakheet Algharbi
- Ibrahim Saud Salh Aldubl
Institutions
- King Fahad Specialist Hospital (SA)
- King Khaled Hospital (SA)
Publication Details
- Journal
- Journal of Ecohumanism
- Published
- 2024-12-12
- DOI
- https://doi.org/10.62754/joe.v3i8.5252
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.12