[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119215-en":3,"doc-seo-119215-105":30,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119215,1099514068035,"Ezra","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",7,"Healthcare","Editorial - Machine learning and immersive technologies for user-centered digital healthcare innovation - User-centered design for digital healthcare innovation","Editorial focuses on how machine learning and immersive technologies (virtual reality, augmented reality, mixed reality) can drive user-centered digital healthcare innovation and improve health and wellbeing. It argues that adoption depends less on technical capability and more on user-centered design choices across ideation, development, and deployment, especially where ethics, trust, and data-driven decision support shape integration into daily routines and clinical workflows. The research topic consolidates interdisciplinary studies and methods to highlight priorities for future R&D.","TYPE Editorial  \nPUBLISHED 14 February 2025 DOI 10. 3389/fdata.2025.1567941  \nOPEN ACCESS  \nEDITED AND REVIEWED BY  \nThomas Hartung,  \nJohns Hopkins University, United States  \n*CORRESPONDENCE  \nFederico Colecchia  \n [federico.colecchia@brunel.ac.uk](federico.colecchia@brunel.ac.uk)  \nRECEIVED 28 January 2025  \nACCEPTED 03 February 2025  \nPUBLISHED 14 February 2025  \nCITATION  \nColecchia F, Giunchi D, Qin R, Ceccaldi E and Wang F (2025) Editorial: Machine learning andimmersive technologies for user-centered digital healthcare innovation.  \nFront. Big Data 8:1567941 .  \ndoi: 10.3389/fdata.2025.1567941  \nCOPYRIGHT  \n© 2025 Colecchia, Giunchi, Qin, Ceccaldi and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nEditorial: Machine learning andimmersive technologies for user-centered digital healthcare innovation  \nFederico Colecchia1*, Daniele Giunchi2 , Rui Qin3 , Eleonora Ceccaldi4 and Fang Wang5  \n1 Brunel Design School, Brunel University of London, Uxbridge, United Kingdom, 2 Department of Computer Science, University College London, London, United Kingdom, 3 School of Computing and Mathematical Sciences, University of Leicester, Leicester, East Midlands, United Kingdom,  \n4 CasaPaganini - InfoMus, DIBRIS, University of Genoa, Genoa, Liguria, Italy, 5 Department of Computer Science, Brunel University of London, Uxbridge, United Kingdom  \nKEYWORDS  \ndigital innovation for health and wellbeing, interdisciplinary collaboration, arti􀀂cial intelligence, immersive technologies, machine learning, virtual reality, augmented reality, mixed reality  \nEditorial on the Research Topic  \nMachine learning and immersive technologies for user-centered digital healthcare innovation  \nUser-centered design for digital healthcare innovation  \nModern digital technologies such as machine learning and immersive technologies, including virtual reality and augmented reality, hold potential for enabling disruptive innovations to promote individuals’ health and wellbeing. However, the adoption of such technologies, including the use of data-driven tools to support healthcare professionals’decision-making and applications relying on consumer electronic devices for the bene􀀂t of individuals, is often hindered by issues that do not necessarily arise from technological limitations but rather are user-centered in nature. Whether new technologies become successfully embedded within individuals’ daily routines and professionals’ work􀀃owsoften depends on the way in which ethical issues directly impacting on user trust have been addressed at the design concept generation, development, and deployment stages.  \nThere is increasing recognition of a need to facilitate further convergence between the development of emerging technologies for promoting individuals’ health and wellbeing and user-centered design research, with a view to achieving positive impact on individuals, care professionals, and healthcare systems. In addressing current development trends relating to user-centered digital innovation for health and wellbeing based on machine learning and immersive technologies, this Research Topic across Frontiers in Arti􀀂cial Intelligence, Frontiers in Virtual Reality, and Frontiers in Big Data has attracted 13 contributions including original research articles, reviews, perspectives, as well as theoretical and methodological contributions, thereby providing a snapshot of recent and ongoing research and development.  \nFrontiersin Big Data 01 [frontiersin.org](frontiersin.org)  \nMachine learning and immersive technologies: a case study  \nWhereas the Research Topic tit","cbCairyhR1oTgVTo","https://ap.wps.com/l/cbCairyhR1oTgVTo","pdf",103835,1,4,"English","en",105,"# Editorial on the Research Topic\n## User-centered design for digital healthcare innovation\n## Machine learning and immersive technologies: a case study\n## Interdisciplinarity, ethics, and stakeholder engagement","[{\"question\":\"What is the main focus of the editorial?\",\"answer\":\"The editorial highlights machine learning and immersive technologies as enablers of user-centered digital healthcare innovation and wellbeing improvements.\"},{\"question\":\"Why is technology adoption often blocked?\",\"answer\":\"Adoption is hindered by user-centered issues—particularly how ethics and trust are handled during design, development, and deployment—rather than by technological limitations alone.\"},{\"question\":\"What kinds of contributions does the research topic include?\",\"answer\":\"It includes original research articles, reviews, perspectives, and theoretical or methodological contributions across related Frontiers journals.\"}]","Editorial - 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