[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-456307-105":59,"doc-detail-456307-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","access-and-reimbursement-for-artificial-intelligence-in-radiology-aosr-perspective","Access and Reimbursement for Artificial Intelligence in Radiology - AOSR Perspective","","Artificial intelligence (AI) is increasingly embedded in diagnostic radiology, enhancing interpretation accuracy and supporting detection and risk assessment. The Asian Oceanian Society of Radiology (AOSR) highlights how AI can improve equity by reducing access gaps between urban and rural communities. The paper reviews adoption disparities across Asia and Oceania, discusses ethical deployment requirements, and examines challenges in reimbursement policies. It outlines AOSR advocacy, educational initiatives, and a collaborative, ethically grounded path toward sustainable AI integration with inclusive benefits for patients.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/access-and-reimbursement-for-artificial-intelligence-in-radiology-aosr-perspective/456307/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/access-and-reimbursement-for-artificial-intelligence-in-radiology-aosr-perspective/456307.png","ImageObject",300,407,{"name":92,"@type":93},"Well Done","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-10","2026-09-30",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",11,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"Why does AOSR emphasize access and reimbursement for AI in radiology?","Question",{"text":113,"@type":114},"AOSR views AI as a bridge between advanced technology and equitable care, aiming to ensure benefits reach both urban and rural communities through supportive reimbursement frameworks.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"What ethical requirements are highlighted for implementing AI in radiology?",{"text":118,"@type":114},"Ethical deployment should include data privacy protection, algorithm transparency, clear clinical responsibility (AI augments rather than replaces judgment), and established standards for safe and responsible integration.",{"name":120,"@type":111,"acceptedAnswer":121},"Which reimbursement policy challenges are identified across Asia and Oceania?",{"text":122,"@type":114},"Despite clinical validation, many countries in the region lack clear reimbursement mechanisms for AI-enabled radiology services, unlike examples from the United States that support emerging technologies.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},456307,1790908661,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":14,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":24,"preview_page_count":4},5909892210082,"https://ap-avatar.wpscdn.com/avatar/56001069da27c9f41e8?x-image-process=image/resize,m_fixed,w_180,h_180&k=1789614185077863061","Editorial  \neISSN 2005-8330  \n[https://doi.org/10.3348/kjr.2025.1645](https://doi.org/10.3348/kjr.2025.1645)[ ](https://doi.org/10.3348/kjr.2025.1645)[Korean J Radiol 2026](Korean J Radiol 2026);[27](27)([1](1))[:7-8](:7-8)  \nAccess and Reimbursement for Artificial Intelligence in Radiology: The Asian Oceanian Society of Radiology Perspective  \nChamaree Chuapetcharasopon  \nDepartment of Radiology, MedPark Hospital, Bangkok, Thailand  \nKeywords: AI in radiology; Reimbursement; Policies; Asia-Oceania  \nINTRODUCTION  \nArtificial intelligence (AI) technologies are increasingly integrated into diagnostic imaging, improving accuracy in interpreting X-rays, stroke detection, and cardiovascular risk assessment. Beyond innovation, AI promises to democratize healthcare access, bridging gaps between urban and rural populations. The Asian Oceanian Society of Radiology (AOSR) envisions AI as a tool to connect advanced technology with equitable care, ensuring no patient is left behind, and presents its perspective largely based on its recent position statements [1] .  \nCURRENT LANDSCAPE IN ASIA AND OCEANIA  \nCountries such as Japan, South Korea, and Singapore lead AI adoption in radiology, supported by robust infrastructure and policy frameworks. In contrast, rural and underserved regions face significant barriers, including limited connectivity and workforce shortages. Addressing these disparities is essential to ensure that AI benefits reach all communities.   \nReceived: November 3, 2025 Accepted: November 4, 2025 Corresponding author: Chamaree Chuapetcharasopon, MD, MBA, Department of Radiology, MedPark Hospital, 3333 Rama IV Road, Klong Toei, Bangkok 10110, Thailand  \n• E-mail: [chamareec@gmail.com](chamareec@gmail.com)  \nThis is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ([https://creativecommons.org/licenses/by-nc/4.0](https://creativecommons.org/licenses/by-nc/4.0)) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.  \nETHICAL CONSIDERATIONS IN AI  \nIMPLEMENTATION  \nEthical deployment of AI in radiology requires:  \n-Data privacy protection: safeguarding patient information to prevent misuse.  \n-Algorithm transparency: ensuring clinicians and patients understand AI decision-making.  \n-Clinical responsibility: AI must augment—not replace—human judgment.  \n-Ethical frameworks: establishing standards for safe and responsible AI integration.  \nCHALLENGES IN REIMBURSEMENT POLICIES  \nDespite clinical validation, many Asia-Oceania countries lack clear reimbursement mechanisms for AIenabled radiology services. In contrast, the United States employs models such as New Technolocy Add-On Payment (NTAP) and Current Procedural Terminology Category III (Category III CPT) codes to support emerging technologies. Demonstrating AI’s value in improving outcomes and reducing costs is critical to avoid innovation stagnation and promote sustainable adoption.  \nAOSR’S ADVOCACY AND ETHICAL FRAMEWORK  \nAOSR promotes:  \n-Core ethical principles: autonomy, beneficence, nonmaleficence, and justice.  \n-Regulatory and reimbursement support: advocating for frameworks that reflect clinical value and performancebased models.  \nCopyright © 2026 The Korean Society of Radiology 7  \n-Public-private partnerships: encouraging collaboration to expand access in low-resource settings.  \n-AI-assisted teleradiology: addressing workforce shortages and improving service delivery.  \nCAPACITY BUILDING AND EDUCATION  \nEmpowering radiologists through continuous education is vital for confident AI adoption. AOSR supports a culture of adaptability, viewing AI as a complement to clinical expertise. Cross-border collaboration fosters shared learning and advances regional radiological practices.  \nCONCLUSION  \nAI is a catalyst for equity, efficiency, and excellence in radiology. Realizing its full potential requires ethical commitment an","cbCaioayU2aueFJp","https://ap.wps.com/l/cbCaioayU2aueFJp","pdf",88656,"English","# Introduction\n# Current Landscape in Asia and Oceania\n# Ethical Considerations in AI Implementation\n# Challenges in Reimbursement Policies\n# AOSR’s Advocacy and Ethical Framework\n# Capacity Building and Education\n# Conclusion","[{\"question\":\"Why does AOSR emphasize access and reimbursement for AI in radiology?\",\"answer\":\"AOSR views AI as a bridge between advanced technology and equitable care, aiming to ensure benefits reach both urban and rural communities through supportive reimbursement frameworks.\"},{\"question\":\"What ethical requirements are highlighted for implementing AI in radiology?\",\"answer\":\"Ethical deployment should include data privacy protection, algorithm transparency, clear clinical responsibility (AI augments rather than replaces judgment), and established standards for safe and responsible integration.\"},{\"question\":\"Which reimbursement policy challenges are identified across Asia and Oceania?\",\"answer\":\"Despite clinical validation, many countries in the region lack clear reimbursement mechanisms for AI-enabled radiology services, unlike examples from the United States that support emerging technologies.\"}]","Access and Reimbursement for Artificial Intelligence in Radiology - AOSR Perspective | PDF",1790745519]