Artificial Intelligence for Radiographers: Basic Principles, Clinical Applications and Implementation Considerations
暫譯: 放射技術人員的人工智慧：基本原則、臨床應用與實施考量
Malamateniou, Christina, Hardy, Maryann, M. Knapp, Karen
相關主題
商品描述
Understanding both technical and practical aspects of AI through case studies enables safe and effective patient care, state-of-the-art academic radiography education, enhanced interdisciplinary team communication and collaboration, and appreciation of the accountability involved when employing AI models.
This textbook also offers insights into the impact on careers, future roles and staff and patient acceptability. It also stresses person-centredness as paramount for AI integration into clinical radiography in a chapter co-produced with patients. Furthermore, it offers the perspectives, supportive statements and AI resources of different national and international organisations, professional bodies and learned societies. Moreover, a chapter led by industry experts brings a unique view on requirements for AI innovation and commercialisation, aiming to inspire hopeful innovators and entrepreneurs.
Finally, the textbook discusses the changing role, responsibilities and competencies of radiographers in a future with AI. It highlights the need to update academic curricula, research priorities and policy to reflect the change of clinical practice and prepare the workforce for a digital future. The editors would like to sincerely thank Dr Charlotte Beardmore, Professor Patrick Brennan, Edward Chan, Samar ElFarra, Dr Kori Stewart, all renowned world leaders in radiography research, education, policy and practice for their kind forewords.
This work is written by the global radiography community as an offering for all radiographers.
商品描述(中文翻譯)
本教科書旨在向放射技術師介紹人工智慧（AI）的基本原則、倫理、治理及其在不同醫學影像模式中的臨床應用，包括AI實施的優勢、挑戰及未來所需的工作。這是所有從事醫學影像和放射治療的臨床實踐者、教育工作者、學者、研究人員和學生的重要資源，提供了一個連貫、基於證據的全面指南，涵蓋當前及未來的實踐。
通過案例研究理解AI的技術和實踐方面，能夠確保安全有效的病人護理、最先進的學術放射技術教育、增強跨學科團隊的溝通與合作，以及對使用AI模型所涉及的責任的認識。
本教科書還提供了對職業影響、未來角色及員工和病人接受度的見解。它強調以人為本的重要性，作為AI整合進臨床放射技術的核心，並與病人共同製作了一章。此外，還提供了不同國家和國際組織、專業機構及學術社團的觀點、支持性聲明和AI資源。此外，由行業專家主導的一章提供了對AI創新和商業化要求的獨特見解，旨在激勵有希望的創新者和企業家。
最後，本教科書討論了在AI未來中放射技術師的角色、責任和能力的變化。它強調需要更新學術課程、研究優先事項和政策，以反映臨床實踐的變化，並為數位未來準備勞動力。
編輯們衷心感謝Dr. Charlotte Beardmore、Professor Patrick Brennan、Edward Chan、Samar ElFarra、Dr. Kori Stewart，這些在放射技術研究、教育、政策和實踐方面的世界知名領袖，為本書所作的前言。
本作品是全球放射技術社群為所有放射技術師所作的貢獻。
作者簡介
Prof. Christina Malamateniou
Christina is a diagnostic radiographer, an Associate Professor and the Director of the CRRa3G research group. She is a world expert on AI in radiography (AI literacy, AI governance, AI leadership and AI impact on the future of professions) and an active researcher over the last 25 years. She has published more than 100 papers with multidisciplinary teams and has a global network of collaborators. She has also developed the first AI module for radiographers, which runs at City St George's, University of London since 2020. Her lifetime research grant income surpasses £3.5 million. She is also an enthusiastic educator. She has been the chair for the Society and College of Radiographers AI working group (2020-2023), the chair of the EFRS research committee (2023-2025) and the first radiographer member at the Board of the European Society of Medical Imaging Informatics (2023-2025).
Prof. Maryann Hardy
Maryann is a diagnostic radiographer, Professor Emerita at the University of Bradford and Director of Radiant Horizons coaching Ltd. Maryann is passionate about radiographers fulfilling their potential in a digital world and her research includes the position of self in human-computer interaction and influence on behaviour. Maryann has developed Radiography and CT simulation programmes for personalised student learning using machine learning algorithms to guide learning needs. She is widely published and was invited by the European Federation of Radiographer Societies to contribute to a joint position statement on Artificial Intelligence for Radiography.
Prof. Karen Knapp
Karen is a diagnostic radiographer and an academic at the University of Exeter. Karen's early research focused on osteoporosis and bone health, but this led her to enter the field of AI research. She has worked in AI with collaborators from computing and mathematics and industry partners for approximately 12 years and within these interdisciplinary teams has helped to develop machine learning and deep learning algorithms for Medical Images. Karen is currently the interim lead for health and wellbeing for the Institute of Data Science and Artificial Intelligence (IDSAI) at the University of Exeter, and has previously been chair of the European Federation of Radiographer Societies (EFRS) Research Committee.
Prof. Aarthi Ramlaul
Aarthi is a diagnostic radiographer and an academic at Buckinghamshire New University. Aarthi's primary research centred on advancing critical thinking within diagnostic radiography education, with a particular focus on how it enhances autonomous clinical decision-making. She maintains a strong interest in the ethico-legal dimensions of professional practice, especially as they intersect with the integration of artificial intelligence in clinical environments. A prolific contributor to the field, Aarthi has edited and authored numerous scholarly works, including five widely used textbooks in medical imaging.
作者簡介(中文翻譯)
克里斯蒂娜·馬拉馬特尼奧教授
克里斯蒂娜是一名診斷放射技術師，副教授及CRRa3G研究小組的主任。她是放射學領域中人工智慧（AI）方面的世界專家（包括AI素養、AI治理、AI領導力及AI對未來職業的影響），並在過去25年中積極從事研究。她與多學科團隊共同發表了超過100篇論文，並擁有全球的合作網絡。她還開發了第一個針對放射技術師的AI模組，自2020年以來在倫敦城市聖喬治大學運行。她的終身研究經費收入超過350萬英鎊。她也是一位熱情的教育者。她曾擔任放射技術師協會和學院AI工作小組的主席（2020-2023），歐洲放射技術師協會（EFRS）研究委員會的主席（2023-2025），以及歐洲醫學影像資訊學會董事會的首位放射技術師成員（2023-2025）。
瑪麗安·哈迪教授
瑪麗安是一名診斷放射技術師，布拉德福德大學名譽教授及Radiant Horizons coaching Ltd.的主任。瑪麗安熱衷於幫助放射技術師在數位世界中發揮潛力，她的研究包括自我在人體與計算機互動中的定位及對行為的影響。瑪麗安開發了放射學和CT模擬課程，利用機器學習算法來指導個性化的學生學習需求。她的發表作品廣泛，並受邀參與歐洲放射技術師協會的聯合立場聲明，針對放射學中的人工智慧進行貢獻。
卡倫·克納普教授
卡倫是一名診斷放射技術師及埃克塞特大學的學者。卡倫早期的研究集中於骨質疏鬆症和骨骼健康，但這使她進入了人工智慧研究領域。她與計算機、數學及行業合作夥伴合作，從事AI研究約12年，並在這些跨學科團隊中幫助開發醫學影像的機器學習和深度學習算法。卡倫目前是埃克塞特大學數據科學與人工智慧研究所（IDSAI）健康與福祉的臨時負責人，並曾擔任歐洲放射技術師協會（EFRS）研究委員會的主席。
阿爾希·拉姆勞教授
阿爾希是一名診斷放射技術師及巴金漢郡新大學的學者。阿爾希的主要研究集中在推進診斷放射學教育中的批判性思維，特別是它如何增強自主臨床決策能力。她對專業實踐的倫理法律維度保持濃厚的興趣，尤其是在人工智慧與臨床環境整合的交集處。作為該領域的多產貢獻者，阿爾希編輯和撰寫了多部學術著作，包括五本廣泛使用的醫學影像教科書。
