[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-456313-105":59,"doc-detail-456313-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-for-artificial-intelligence-in-radiology-a-hong-kong-perspective","Access for Artificial Intelligence in Radiology - A Hong Kong Perspective","","AI, when applied appropriately, can support radiologists and improve patient care across diagnostic and interventional radiology by prioritizing reporting and clinical management while targeting limited manpower toward high-need areas. In Hong Kong, AI has become increasingly embedded in radiology workflows, particularly within the public system serving over 90% of patients. Accessibility depends on compatibility with existing practices and platforms, adaptability to user needs, infrastructure availability, and cost. Examples include AI integrated with CMS to flag suspicious findings, support review through RIS and PACS links, and reduce variability in automated bone-age assessment, while assisting emergency triage for CT hemorrhage and accelerating stroke team coordination.",{"@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-for-artificial-intelligence-in-radiology-a-hong-kong-perspective/456313/",{"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-for-artificial-intelligence-in-radiology-a-hong-kong-perspective/456313.png","ImageObject",300,407,{"name":92,"@type":93},"Fans","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","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},"How can AI help radiologists and benefit patients?","Question",{"text":113,"@type":114},"AI can assist radiologists in both diagnostic and interventional radiology by prioritizing reporting, facilitating clinical management, focusing limited manpower on needy areas, and supporting earlier detection and decision-making.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"What factors determine whether AI is accessible and widely used?",{"text":118,"@type":114},"Accessibility and utilization depend on compatibility with existing practices and platforms, adaptability to user needs, availability of appropriate infrastructure, and cost.",{"name":120,"@type":111,"acceptedAnswer":121},"Why is radiologist review still necessary when AI is used?",{"text":122,"@type":114},"No system is perfect; false positives and false negatives can occur. Radiologists must review, confirm, dismiss, and recommend follow-up imaging such as X-rays or CT.","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},456313,1791030603,{"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},5909892330395,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","Editorial  \neISSN 2005-8330  \n[https://doi.org/10.3348/kjr.2025.1655](https://doi.org/10.3348/kjr.2025.1655)[ ](https://doi.org/10.3348/kjr.2025.1655)[Korean J Radiol 2026](Korean J Radiol 2026);[27](27)([1](1))[:9-10](:9-10)  \nAccess for Artificial Intelligence in Radiology: A Hong Kong Perspective  \nBilly Ming-Hei Lai  \nDepartment of Imaging and Interventional Radiology, Prince of Wales Hospital, Sha Tin, Hong Kong SAR  \nKeywords: Artificial intelligence; Quality assurance; Human-AI interaction  \nWithout doubt, when utilized appropriately, artificial intelligence (AI) can help radiologists and benefit patients. AI can assist the radiologist in many ways, in both diagnostic and interventional radiology, helping to prioritize reporting, facilitate clinical management, concentrate expertise, focus limited manpower resources to needy areas and, at times, can also aid to increase confidence for the reporting radiologist.  \nIn Hong Kong, AI has become an increasingly integral part of the radiology workflow, especially in the public system, which serves more than 90% of the patients.  \nThere are a number of factors which influence accessibility and utilization of AI, such as, compatibility with existing practices and platforms, adaptability to user needs, presence of appropriate infrastructure, and cost.  \nLike many places worldwide, there are separate existing platforms utilized by clinicians and radiologists for dayto-day workflow. In Hong Kong, the Clinical Management System (CMS) is used mainly by clinicians for everyday operations, such as clinical note taking and prescription. The Radiology Information System (RIS) and Picture  \nReceived: October 31, 2025 Accepted: November 4, 2025 Corresponding author: Billy Ming-Hei Lai, MBBS, MResMed, FRCR, FHKCR, FHKAM (Radiology), Department of Imaging and Interventional Radiology, Prince of Wales Hospital, 30-32 Ngan Shing Street, Sha Tin, Hong Kong SAR  \n• E-mail: [billymhlai@cuhk.edu.hk](billymhlai@cuhk.edu.hk)  \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.  \nArchiving and Communication System (PACS) are used by radiologists for reporting, imaging processing, for handling clinical referrals and logistics for imaging and interventional procedures. These systems share common linkages at some points but are different in layout and functions.  \nChest X-ray is one of the most commonly prescribed imaging tests in practice. There are many areas in which AI has been deployed to aid clinicians and radiologists in the detection of various abnormalities. In Hong Kong, we have implemented AI in our general outpatient family medicine clinics and emergency departments, which need to handle a large number of requests daily and, frequently, are the first line in providing medical care for patients. The AI has been integrated into the CMS and aids clinicians in identifying important suspicious findings, such as lung nodules and masses, pneumothorax, pleural effusions, and abnormal line placements, which in turn allows earlier detection and clinical management, appropriate referral and further work up if needed.  \nUnderstandably, no system is perfect, and there  \nwill be false positives and false negatives, which will require radiologists’ review for confirmation, dismissal, or recommendation for follow up x-rays or computed tomography (CT) . Hence it is important that the AI system is accessible to the radiologist, or better yet, integrated into RIS and PACS, so as to allow radiologists to visualize the area where suspected abnormality is located, hence permitting appropriate review and facilitating better communication with the clinician.  \nEvaluation of bone age is a common request for pediatri","cbCaigO674CVsNkQ","https://ap.wps.com/l/cbCaigO674CVsNkQ","pdf",83802,"English","# Access for Artificial Intelligence in Radiology: A Hong Kong Perspective\n## AI benefits in radiology and patient care\n## Factors influencing AI accessibility and utilization\n## Integration across CMS, RIS, and PACS\n## Clinical applications in Hong Kong (outpatient, emergency, imaging types)\n## Limitations and need for radiologist review\n## Automated bone-age evaluation and variability reduction\n## Emergency CT hemorrhage detection and triage\n## AI support for acute ischemic stroke workflows","[{\"question\":\"How can AI help radiologists and benefit patients?\",\"answer\":\"AI can assist radiologists in both diagnostic and interventional radiology by prioritizing reporting, facilitating clinical management, focusing limited manpower on needy areas, and supporting earlier detection and decision-making.\"},{\"question\":\"What factors determine whether AI is accessible and widely used?\",\"answer\":\"Accessibility and utilization depend on compatibility with existing practices and platforms, adaptability to user needs, availability of appropriate infrastructure, and cost.\"},{\"question\":\"Why is radiologist review still necessary when AI is used?\",\"answer\":\"No system is perfect; false positives and false negatives can occur. Radiologists must review, confirm, dismiss, and recommend follow-up imaging such as X-rays or CT.\"}]","Access for Artificial Intelligence in Radiology - A Hong Kong Perspective | PDF",1790745528]