Artificial intelligence in medicine and healthcare: a review and classification of current and near-future applications and their ethical and social Impact
Universidad de Sevilla（塞维利亚大学）；Institute of Biomedicine of Seville (IBIS)（塞维利亚生物医学研究所）；Royal Academy of Medicine and Surgery of Seville（塞维利亚皇家医学与外科学院）；Joint Research Center, European Commission（欧盟委员会联合研究中心）；Universitat Pompeu Fabra（庞培法布拉大学）；Hospital Universitario “Virgen del Rocio”（“罗西圣母”大学医院）；Center for Advanced Neurology (CNA)（高级神经病学中心）；Hospital Universitario “Virgen Macarena”（“马卡雷纳圣母”大学医院）；Instituto de Salud Carlos III (ISCIII)（卡洛斯三世卫生研究所）；College of Medicine, Universidad de Sevilla（塞维利亚大学医学院）；Hospital “VITHAS-NISA Sevilla”（塞维利亚VITHAS-NISA医院）；DINAC Foundation（DINAC基金会）
Emilio Gómez-González, Emilia Gomez, Javier Márquez-Rivas, Manuel Guerrero-Claro, Isabel Fernández-Lizaranzu, María Isabel Relimpio-López, Manuel E. Dorado, Mar… 展开作者
Emilio Gómez-González, Emilia Gomez, Javier Márquez-Rivas, Manuel Guerrero-Claro, Isabel Fernández-Lizaranzu, María Isabel Relimpio-López, Manuel E. Dorado, María José Mayorga-Buiza, Guillermo Izquierdo-Ayuso, Luis Capitán-Morales
This paper provides an overview of the current and near-future applications of Artificial Intelligence (AI) in Medicine and Health Care and presents a classification according to their ethical and societal aspects, potential benefits and pitfalls, and issues that can be considered controversial and are not deeply discussed in the literature.
This work is based on an analysis of the state of the art of research and technology, including existing software, personal monitoring devices, genetic tests and editing tools, personalized digital models, online platforms, augmented reality devices, and surgical and companion robotics. Motivated by our review, we present and describe the notion of 'extended personalized medicine', we then review existing applications of AI in medicine and healthcare and explore the public perception of medical AI systems, and how they show, simultaneously, extraordinary opportunities and drawbacks that even question fundamental medical concepts. Many of these topics coincide with urgent priorities recently defined by the World Health Organization for the coming decade. In addition, we study the transformations of the roles of doctors and patients in an age of ubiquitous information, identify the risk of a division of Medicine into 'fake-based', 'patient-generated', and 'scientifically tailored', and draw the attention of some aspects that need further thorough analysis and public debate.
The dawn of the digital medicine era, ushered in by increasingly powerful embedded systems and Internet of Things (IoT) computing devices, is creating new therapies and biomedical solutions that promise to positively transform our quality of life. However, the digital medicine revolution also creates unforeseen and complex ethical, regulatory, and societal issues. In this article, we reflect on the ethical challenges facing digital medicine. We discuss the perils of ethical oversights in medical devices, and the role of professional codes and regulatory oversight towards the ethical design, de…
Data Ethics in the Era of Healthcare Artificial Intelligence in Africa: An Ubuntu Philosophy Perspective
Stanford Center for Biomedical Ethics, Stanford University（斯坦福大学生物医学伦理中心）；Department of Bioethics and Interdisciplinary Studies, Brody School of Medicine, East Carolina University（东卡罗来纳大学布罗迪医学院生物伦理与跨学科研究系）；Department of Biomedical Data Science, Stanford University（斯坦福大学生物医学数据科学系）；Department of Bioengineering, Stanford University（斯坦福大学生物工程系）；Department of Genetics, Stanford University（斯坦福大学遗传学系）；Department of Medicine, Stanford University（斯坦福大学医学系）
本文针对西方医疗 AI 数据伦理框架忽视非洲文化与殖民历史的问题，从 Ubuntu 哲学出发比较个人主义与社群主义路径，提出面向非洲的医疗数据伦理框架。
Imperial College London（帝国理工学院）；University of Bayreuth（拜罗伊特大学）
An appropriate ethical framework around the use of Artificial Intelligence (AI) in healthcare has become a key desirable with the increasingly widespread deployment of this technology. Advances in AI hold the promise of improving the precision of outcome prediction at the level of the individual. However, the addition of these technologies to patient-clinician interactions, as with any complex human interaction, has potential pitfalls. While physicians have always had to carefully consider the ethical background and implications of their actions, detailed deliberations around fast-moving techn…
This article reviews the landscape of ethical challenges of integrating artificial intelligence (AI) into smart healthcare products, including medical electronic devices. Differences between traditional ethics in the medical domain and emerging ethical challenges with AI-driven healthcare are presented, particularly as they relate to transparency, bias, privacy, safety, responsibility, justice, and autonomy. Open challenges and recommendations are outlined to enable the integration of ethical principles into the design, validation, clinical trials, deployment, monitoring, repair, and retiremen…
As the population grows, the need for a quality level of medical services grows correspondingly, so does the demand for information technology in medicine. The concept of "Smart Healthcare" offers many approaches aimed at solving the acute problems faced by modern healthcare. In this paper, we review the main problems of modern healthcare, analyze existing approaches and technologies in the areas of digital twins, the Internet of Things and mobile medicine, determine their effectiveness in solving the set problems, consider the technologies that are used to monitor and treat patients and propo…
Generative Artificial Intelligence in Healthcare: Ethical Considerations and Assessment Checklist
Duke-NUS Medical School（杜克-新加坡国立大学医学院）；National University of Singapore（新加坡国立大学）；University of Oxford（牛津大学）；Imperial College London（帝国理工学院）；University of Antwerp（安特卫普大学）；Singapore Eye Research Institute（新加坡眼科研究所）；Singapore National Eye Centre（新加坡全国眼科中心）；Singapore Health Services（新加坡保健服务）；Singapore General Hospital（新加坡中央医院）；Hangzhou Dianzi University（杭州电子科技大学）；Nanyang Technological University（南洋理工大学）；The Chinese University of Hong Kong（香港中文大学）；Scripps Research（斯克里普斯研究所）
From Military to Healthcare: Adopting and Expanding Ethical Principles for Generative Artificial Intelligence
University of Pittsburgh（匹兹堡大学）；Weill Cornell Medicine（威尔康奈尔医学院）；Telemedicine & Advanced Technology Research Center, US Army（美国陆军远程医疗与先进技术研究中心）；Uniformed Services University（美国卫生与公众服务部统一服务大学）；Brooke Army Medical Center（布鲁克陆军医学中心）；University of Pittsburgh Medical Center Hillman Cancer Center（匹兹堡大学医学中心希尔曼癌症中心）
American University of the Middle East（美国中东大学）；University of Toronto（多伦多大学）
This paper presents a new approach to prevent transportation accidents and monitor driver's behavior using a healthcare AI system that incorporates fairness and ethics. Dangerous medical cases and unusual behavior of the driver are detected. Fairness algorithm is approached in order to improve decision-making and address ethical issues such as privacy issues, and to consider challenges that appear in the wild within AI in healthcare and driving. A healthcare professional will be alerted about any unusual activity, and the driver's location when necessary, is provided in order to enable the hea…
Agentic AI in Healthcare & Medicine: A Seven-Dimensional Taxonomy for Empirical Evaluation of LLM-based Agents
Department of Computer Science, New York University, CIMS, New York, USA（纽约大学计算机科学系，CIMS，纽约，美国）；Department of Computer Science, Cleveland State University, Cleveland, USA（克利夫兰州立大学计算机科学系，克利夫兰，美国）
The potential role of AI agents in transforming nuclear medicine research and cancer management in India
Australian Institute for Bioengineering and Nanotechnology（澳大利亚生物工程与纳米技术研究所）；The University of Queensland（昆士兰大学）；Rohtak Nuclear Medcare Imaging Therapy and Research Center（罗塔克核医学影像治疗与研究中心）；Apollo Multispeciality Hospital（阿波罗 multispeciality 医院）；Apollo Hospitals Educational and Research Foundation（阿波罗医院教育与研究基金会）；Australian eHealth Research Centre（澳大利亚电子健康研究中心）；CSIRO（联邦科学与工业研究组织）；Georgia Institute of Technology（佐治亚理工学院）
We are moving towards a future where Artificial Intelligence (AI) based agents make many decisions on behalf of humans. From healthcare decision making to social media censoring, these agents face problems, and make decisions with ethical and societal implications. Ethical behaviour is a critical characteristic that we would like in a human-centric AI. A common observation in human-centric industries, like the service industry and healthcare, is that their professionals tend to break rules, if necessary, for pro-social reasons. This behaviour among humans is defined as pro-social rule breaking…
Towards Clinical AI Fairness: Filling Gaps in the Puzzle
Duke-NUS Medical School（杜克-新加坡国立大学医学院）；University of Birmingham（伯明翰大学）；University Hospitals Birmingham NHS Foundation Trust（伯明翰大学医院NHS基金会信托）；National Institute for Health and Care Research Birmingham Biomedical Research Centre（国家健康与护理研究所伯明翰生物医学研究中心）；University of Antwerp（安特卫普大学）；University of Florida（佛罗里达大学）；Singapore Eye Research Institute（新加坡眼科研究所）；Singapore National Eye Centre（新加坡国家眼科中心）；Singapore General Hospital（新加坡中央医院）；Weill Cornell Medicine（威尔康奈尔医学院）；Massachusetts Institute of Technology（麻省理工学院）；Beth Israel Deaconess Medical Center（贝斯以色列女执事医疗中心）；Harvard T.H. Chan School of Public Health（哈佛大学陈曾熙公共卫生学院）；National University of Singapore（新加坡国立大学）
Jahangirnagar University（贾汉吉尔纳加尔大学）；CSIRO（澳大利亚联邦科学与工业研究组织）；Queensland University of Technology（昆士兰科技大学）；University of the Sunshine Coast（阳光海岸大学）；Sylhet MAG Osmani Medical College（锡尔赫特MAG奥斯马尼医学院）
The recent advances of Augmented Reality (AR) in healthcare have shown that technology is a significant part of the current healthcare system. In recent days, augmented reality has proposed numerous smart applications in healthcare domain including wearable access, telemedicine, remote surgery, diagnosis of medical reports, emergency medicine, etc. The aim of the developed augmented healthcare application is to improve patient care, increase efficiency, and decrease costs. This article puts on an effort to review the advances in AR-based healthcare technologies and goes to peek into the strate…
Artificial Intelligence (AI) is transforming our daily life with several applications in healthcare, space exploration, banking and finance. These rapid progresses in AI have brought increasing attention to the potential impacts of AI technologies on society, with ethically questionable consequences. In recent years, several ethical principles have been released by governments, national and international organisations. These principles outline high-level precepts to guide the ethical development, deployment, and governance of AI. However, the abstract nature, diversity, and context-dependency …
Abdul Latif Jameel Clinic for Machine Learning in Health, MIT（麻省理工学院阿卜杜勒·拉蒂夫·贾米勒健康机器学习诊所）；Wyss Institute for Biologically Inspired Engineering, Harvard University（哈佛大学怀斯生物启发工程研究所）；Operations Research Center, Massachusetts Institute of Technology (MIT)（麻省理工学院运筹学研究中心）；Sloan School of Management, MIT（麻省理工学院斯隆管理学院）
Artificial intelligence (AI) systems hold great promise to improve healthcare over the next decades. Specifically, AI systems leveraging multiple data sources and input modalities are poised to become a viable method to deliver more accurate results and deployable pipelines across a wide range of applications. In this work, we propose and evaluate a unified Holistic AI in Medicine (HAIM) framework to facilitate the generation and testing of AI systems that leverage multimodal inputs. Our approach uses generalizable data pre-processing and machine learning modeling stages that can be readily ad…
Getting Ready for the EU AI Act in Healthcare. A call for Sustainable AI Development and Deployment
University of Copenhagen（哥本哈根大学）；UiT The Arctic University of Norway（挪威北极圈大学）；Arcada University of Applied Science（阿卡达应用科学大学）；QUEST Centre for Responsible Research, Berlin Institute of Health, Charité - Universitätsmedizin Berlin（QUEST负责任研究中心，柏林健康研究所，柏林夏里特医学院）；Karolinska Institutet（卡罗林斯卡学院）；Stockholm Health Care Services, Region Stockholm（斯德哥尔摩地区医疗保健服务）；CIRSFID-Alma AI, University of Bologna（CIRSFID-Alma AI，博洛尼亚大学）；EUI（欧洲大学研究院）；Stockholm University（斯德哥尔摩大学）；Graduate School of Data Science, Seoul National University（数据科学研究生院，首尔国立大学）
University College London（伦敦大学学院）；NIHR University College London Hospitals Biomedical Research Centre（英国国家健康研究所伦敦大学学院医院生物医学研究中心）；McGill University（麦吉尔大学）
Equity is widely held to be fundamental to the ethics of healthcare. In the context of clinical decision-making, it rests on the comparative fidelity of the intelligence -- evidence-based or intuitive -- guiding the management of each individual patient. Though brought to recent attention by the individuating power of contemporary machine learning, such epistemic equity arises in the context of any decision guidance, whether traditional or innovative. Yet no general framework for its quantification, let alone assurance, currently exists. Here we formulate epistemic equity in terms of model fid…
Artificial Intelligence (AI) and Medical Humanities have become two of the most crucial and rapidly growing fields in the current world. AI has made substantial advancements in recent years, enabling the development of algorithms and systems that can perform tasks traditionally done by humans. Medical Humanities, on the other hand, is the intersection of medical sciences, humanities, and the social sciences, and deals with the cultural, historical, philosophical, ethical, and social aspects of health, illness, and medicine. The integration of AI and Medical Humanities can offer innovative solu…
NTNU（挪威科技大学）；SimulaMet（SimulaMet 研究所）；University of Bergen（卑尔根大学）；Berlin Institute of Health (BIH)（柏林健康研究所）；Charité Universitätsmedizin Berlin（柏林夏里特医学院）；Birmingham City University（伯明翰城市大学）
While the demand for ethical artificial intelligence (AI) systems increases, the number of unethical uses of AI accelerates, even though there is no shortage of ethical guidelines. We argue that a possible underlying cause for this is that AI developers face a social dilemma in AI development ethics, preventing the widespread adaptation of ethical best practices. We define the social dilemma for AI development and describe why the current crisis in AI development ethics cannot be solved without relieving AI developers of their social dilemma. We argue that AI development must be professionalis…
Several problems in healthcare stem from the complex network of intermediaries and the lack of traceability of transactions. To mention a few: healthcare data is fragmented across several silos negatively affecting research and services, about half of the clinical trials are never reported, the cost of drug discovery is ever increasing, and substandard and fake medicines are still a huge problem. Blockchain has the potential to solve these problems as it provides trust without any intermediaries, has traceability as a default feature, and promises new business models by enabling novel incentiv…
Facultat de Filosofia, Universitat de Barcelona (UB)（巴塞罗那大学哲学系）
Social robotics development for the practice of care and European prospects to incorporate these AI-based systems in institutional healthcare contexts call for an urgent ethical reflection to (re)configurate our practical life according to human values and rights. Despite the growing attention to the ethical implications of social robotics, the current debate on one of its central branches, social assistive robotics (SAR), rests upon an impoverished ethical approach. This paper presents and examines some tendencies of this prevailing approach, which have been identified as a result of a critic…
University of Augsburg（奥格斯堡大学）；Centre for Interdisciplinary Health Research（跨学科健康研究中心）；Medical University of Graz（格拉茨医科大学）
Recent years have seen a rapid increase in digital medicine research in an attempt to transform traditional healthcare systems to their modern, intelligent, and versatile equivalents that are adequately equipped to tackle contemporary challenges. This has led to a wave of applications that utilise AI technologies; first and foremost in the fields of medical imaging, but also in the use of wearables and other intelligent sensors. In comparison, computer audition can be seen to be lagging behind, at least in terms of commercial interest. Yet, audition has long been a staple assistant for medical…
Explainability matters: The effect of liability rules on the healthcare sector
Department of Mechanical Engineering, National University of Singapore（新加坡国立大学机械工程系）；Dipartimento di Giurisprudenza, Università di Pisa（比萨大学法学院）；Dirpolis Institute, Scuola Superiore Sant’Anna（圣安娜高等学院Dirpolis研究所）；Department of Mathematics (courtesy), National University of Singapore（新加坡国立大学数学系）
