The future of Radiology: (Record no. 16976)

000 -LEADER
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001 - CONTROL NUMBER
control field 16976
003 - CONTROL NUMBER IDENTIFIER
control field OCLRC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260731013050.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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040 ## - CATALOGING SOURCE
Original cataloging agency OCLRC
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number (Call Number) T 616.07572 2025 0067
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Tablate, Tony Jasper
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Reyes, Natalie Andrei F.
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Gallardo, Aaron John I.
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Cantor, Jeoven Samuel G.
245 ## - TITLE STATEMENT
Title The future of Radiology:
Sub Title AI in enhancing x-ray imaging techniques and for diagnostic accurancy/
Statement of responsibility, etc. Jeoven Samuel G. Cantor, Aaron John L. Gallardo, Natalie Andrei F. Reyes, & Tony Jasper Tablate.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc. Parañaque City:
Name of publisher, distributor, etc. Olivarez College,
Date of publication, distribution, etc. 2025.
502 ## - DISSERTATION NOTE
Dissertation note Undergraduate thesis.
520 ## - SUMMARY, ETC.
Summary, etc. 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.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Subject Entry artificial intelligence
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Subject Entry radiologists technologist
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Subject Entry radiology
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Subject Entry CT imaging
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Subject Entry X-ray imaging
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Subject Entry phenomenology
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Subject Entry workflow
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Subject Entry treatment
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Theses/Dissertation
Location (call number prefix code) T 616.07572 2025 0067
Holdings
Withdrawn status Lost status Piece physical condition (Damaged Status) Not for loan Home library Current library (holdingbranch) Date acquired Total checkouts Full call number Date last seen Price effective from Koha item type
        Olivarez College Learning Resource Center General Reference And Serial Section 07/31/2026   T 616.07572 2025 0067 07/31/2026 07/31/2026 Theses/Dissertation