Current Trends and Future Prospects of Artificial Intelligence in Transforming Radiology

• DOI: 10.47679/jchs.202487
• Publication Date: 2024-12-05T15:33:18Z
• Authors: Rezwan Ahmed Mahedi; Hrishik Iqbal; Raiyan Azmee; Marzan Azmee; Fatiha Jakir; Mufassir Ahmad Ni...; Mohammed Burhan U...; Sadia Afrin
• Keywords: Triage; Identification

Artificial intelligence (AI) has rapidly transformed numerous industries, including medicine, with radiography standing to benefit significantly from its capabilities. AI enhances diagnostic accuracy, reduces errors, and improves patient care by leveraging large datasets digital radiographs commonly used in medical dental practices. Despite these advantages, the impact of on image acquisition radiographer workflows remains underexplored literature. This review aims evaluate effects radiographic practices, address regulatory challenges, explore integration into educational frameworks for radiologists radiographers. It highlights AI's role automating tasks, enhancing precision, improving clinical decision-making. A systematic literature search was conducted using PubMed Google Scholar up December 2024, terms "artificial intelligence," "machine learning," "deep "radiography," "diagnostic imaging." Seventy-seven peer-reviewed articles conference papers focusing applications were analyzed extract data methodologies their potential applications. The findings reveal that AI-powered solutions enhance efficiency complex imaging such as lesion identification triage mammography, real-time assessments cross-sectional imaging, reducing need re-scans increasing throughput. However, widespread adoption faces obstacles related ethical legal concerns, privacy, algorithmic bias, transparency. While demonstrates significant automate workflows, improve optimize radiography, challenges human oversight, professional adaptation, compliance must be addressed. Further research is needed fully understand AI’s maximize utility.