03163nam a22003137a 4500 16976 OCLRC 20260731013050.0 260624t xxu||||| |||| 00| 0 eng d OCLRC T 616.07572 2025 0067 Tablate, Tony Jasper The future of Radiology: AI in enhancing x-ray imaging techniques and for diagnostic accurancy/ Jeoven Samuel G. Cantor, Aaron John L. Gallardo, Natalie Andrei F. Reyes, & Tony Jasper Tablate. Parañaque City: Olivarez College, 2025. Undergraduate thesis. This qualitative research delves into the experiences of radiologists and Radiologic Technologists in employing Artificial Intelligence (AI) in medical imaging, with emphasis on CT scans in tertiary hospitals in the National Capital Region (NCR) of the Philippines. The integration of AI in Radiology promises to enhance diagnostic accuracy, optimize workflow efficiency and minimize human error. Yet, challenges persist as far as user adaptation, trust, and balance between AI support and human skill are connected. With a phenomenological study design, semi-structured in-depth interviews were carried out among seven purposely selected radiology professionals to gain an understanding of their subjective experiences, perceptions, and challenges with AI deployment. The research sought to determine major themes concerning the influence of A on medical imaging practice. Results indicated that AI greatly enhances productivity and diagnostic assistance through automated image segmentation and processing, supporting radiologists in detecting abnormalities with increased confidence and at faster speeds. Radiologic technologists welcomed the ease of operation and efficiency that AI introduces into workflow management but also noted fear of overdependence and compromise on clinical competence. Participants underscored the critical value of human judgement and pointed to the necessity of constant monitoring to guarantee the accuracy and dependability of AI outputs. Other new themes that emerged were ease of operation, faith in AI technology, the possibility of innovation, and ethical accountability in AI use. In summary, although AI has been perceived to be an excellent tool that augments Radiologic Practice, it needs to be done thoughtfully and in balance with human know-how to ensure quality patient care. This research reiterates the necessity of customized training, user interaction and continued monitoring to ensure adoption of AI in medical imaging. Further research is recommended to expand understanding of AI{92}s roles across diverse clinical settings and to address region-specific challenges in the Philippines. artificial intelligence radiologists technologist radiology CT imaging X-ray imaging phenomenology workflow treatment Reyes, Natalie Andrei F. Gallardo, Aaron John I. Cantor, Jeoven Samuel G. THES T 616.07572 2025 0067 16976 16976 0 0 0 0 LRC GR 2026-07-31 0 T 616.07572 2025 0067 2026-07-31 01:30:50 2026-07-31 THES