{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T06:15:23Z","timestamp":1788243323336,"version":"build-2803163510"},"reference-count":76,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Digit. Health"],"abstract":"<jats:p>Medicine is a predominantly physical profession, yet most medical artificial intelligence (AI) remains screen bound. Physical artificial intelligence (PAI) extends AI's capabilities and can directly address many of the healthcare system challenges and unmet needs such as workforce shortages, unsustainable healthcare costs, heightened expectations, aging population and need for pandemic preparedness. PAI relies on systems that autonomously perceive, decide, and actuate in real-time by synthesizing diverse environmental data from multiple sensory sources. These data undergo rapid processing and interpretation, facilitating immediate decision-making and responsive physical actions, including movement, object manipulation, and direct human interaction. This paper first identifies critical healthcare system needs that robotic agents can effectively address. It further examines core actions of PAI systems, emphasizing perceptual pathways, clinical decision-making processes, and human-robot interactions that translate sensory inputs into tailored, patient-specific responses. We explore essential data utilization aspects, including edge-device advances, PAI datasets, digital twins, and edge-to-cloud infrastructures that support real-time inference and are crucial for reducing barriers to PAI implementation. Finally, we analyze the cultural factors accelerating the adoption of PAI in healthcare and review PAI advancements in other sectors. We argue that the convergence of pressing healthcare demands, technological advancements, and cultural readiness signals a tipping point for PAI in medicine.<\/jats:p>","DOI":"10.3389\/fdgth.2026.1914012","type":"journal-article","created":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T05:36:00Z","timestamp":1788240960000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Convergence of need technology and culture driving the era of physical AI in medicine"],"prefix":"10.3389","volume":"8","author":[{"given":"Yonatan","family":"Prat","sequence":"first","affiliation":[{"name":"Department of Urology, Sheba Medical Center, Tel HaShomer","place":["Ramat Gan, Israel"]},{"name":"ARC Innovation Center, Sheba Medical Center, Tel HaShomer","place":["Ramat Gan, Israel"]},{"name":"Gray Faculty of Medical & Health Sciences, Tel Aviv University","place":["Tel Aviv-Yafo, Israel"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roee","family":"Francos","sequence":"additional","affiliation":[{"name":"Harvard John A Paulson School of Engineering and Applied Sciences","place":["Cambridge, MA, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Moshe","family":"Shoham","sequence":"additional","affiliation":[{"name":"Faculty of Mechanical Engineering, Technion, Israel Institute of Technology","place":["Haifa, Israel"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eyal","family":"Zimlichman","sequence":"additional","affiliation":[{"name":"ARC Innovation Center, Sheba Medical Center, Tel HaShomer","place":["Ramat Gan, Israel"]},{"name":"Gray Faculty of Medical & Health Sciences, Tel Aviv University","place":["Tel Aviv-Yafo, Israel"]},{"name":"Dina Recanati School of Medicine, Reichman University","place":["Herzliya, Israel"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abraham","family":"Tsur","sequence":"additional","affiliation":[{"name":"ARC Innovation Center, Sheba Medical Center, Tel HaShomer","place":["Ramat Gan, Israel"]},{"name":"Dina Recanati School of Medicine, Reichman University","place":["Herzliya, Israel"]},{"name":"Gynecology Oncology Department, The Josef Buchmann Gynecology and Maternity Center","place":["Tel HaShomer, Israel"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,1]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1038\/s41591-018-0300-7","article-title":"High-performance medicine: the convergence of human and artificial intelligence","volume":"25","author":"Topol","year":"2019","journal-title":"Nat Med"},{"key":"B2","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1377\/hlthaff.2024.01003","article-title":"Artificial intelligence in health and health care: priorities for action: article examines priorities for the uses of artificial intelligence in health and health care","volume":"44","author":"Matheny","year":"2025","journal-title":"Health Aff"},{"key":"B3","doi-asserted-by":"publisher","first-page":"491","DOI":"10.1038\/s42256-026-01239-3","article-title":"From embodied intelligence to physical AI","volume":"8","year":"2026","journal-title":"Nat Mach Intell"},{"key":"B4","doi-asserted-by":"publisher","first-page":"1282","DOI":"10.1038\/s41586-026-10675-5","article-title":"Towards autonomous medical artificial intelligence agents","volume":"655","author":"Ferber","year":"2026","journal-title":"Nature"},{"key":"B5","doi-asserted-by":"publisher","first-page":"592","DOI":"10.1038\/s42256-025-01005-x","article-title":"Embodied large language models enable robots to complete complex tasks in unpredictable environments","volume":"7","author":"Mon-Williams","year":"2025","journal-title":"Nat Mach Intell"},{"key":"B6","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1038\/s41746-024-01102-y","article-title":"Levels of autonomy in FDA-cleared surgical robots: a systematic review","volume":"7","author":"Lee","year":"2024","journal-title":"npj Digit Med"},{"key":"B7","doi-asserted-by":"publisher","first-page":"745","DOI":"10.1109\/TCE.2023.3293993","article-title":"Healthcare 5.0: in the perspective of consumer internet-of-things-based fog\/cloud computing","volume":"69","author":"Chi","year":"2023","journal-title":"IEEE Trans Consumer Electron"},{"key":"B8","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1038\/s41591-023-02732-7","article-title":"The IDEAL framework for surgical robotics: development, comparative evaluation and long-term monitoring","volume":"30","author":"Marcus","year":"2024","journal-title":"Nat Med"},{"key":"B9","doi-asserted-by":"publisher","first-page":"CAT.24.0496","DOI":"10.1056\/CAT.24.0496","article-title":"Health care workforce challenges persist as a legacy of COVID-19","volume":"6","author":"Cerise","year":"2024","journal-title":"NEJM Catalyst"},{"key":"B10","doi-asserted-by":"publisher","first-page":"e009316","DOI":"10.1136\/bmjgh-2022-009316","article-title":"The global health workforce stock and distribution in 2020 and 2030: a threat to equity and \u2018universal\u2019 health coverage?","volume":"7","author":"Boniol","year":"2022","journal-title":"BMJ Glob Health"},{"key":"B11","doi-asserted-by":"publisher","first-page":"662","DOI":"10.1002\/ijgo.15018","article-title":"Integrating technologies to provide comprehensive remote fetal surveillance: a prospective pilot study","volume":"164","author":"Nir","year":"2024","journal-title":"Intl J Gynecology & Obste"},{"key":"B12","doi-asserted-by":"publisher","first-page":"288","DOI":"10.1002\/nur.20383","article-title":"Nurse burnout and quality of care: cross-national investigation in six countries","volume":"33","author":"Poghosyan","year":"2010","journal-title":"Res Nurs Health"},{"key":"B13","doi-asserted-by":"publisher","first-page":"e0159015","DOI":"10.1371\/journal.pone.0159015","article-title":"Healthcare staff wellbeing, burnout, and patient safety: a systematic review","volume":"11","author":"Hall","year":"2016","journal-title":"PLoS One"},{"key":"B14","doi-asserted-by":"publisher","first-page":"910","DOI":"10.1377\/hlthaff.2024.00469","article-title":"National health expenditure projections, 2023\u201332: payer trends diverge as pandemic-related policies fade: study examines national health expenditure projections, 2023\u201332","volume":"43","author":"Fiore","year":"2024","journal-title":"Health Aff"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2405.02957","article-title":"Agent hospital: a simulacrum of hospital with evolvable medical agents","author":"Yang Liu","year":"2024"},{"key":"B16","doi-asserted-by":"publisher","first-page":"e232255","DOI":"10.1148\/radiol.232255","article-title":"Collaborative enhancement of consistency and accuracy in US diagnosis of thyroid nodules using large language models","volume":"310","author":"Wu","year":"2024","journal-title":"Radiology"},{"key":"B17","doi-asserted-by":"crossref","DOI":"10.1109\/IROS45743.2020.9340913","article-title":"Ultrasound-Guided robotic navigation with deep reinforcement learning","author":"Hase","year":"2020"},{"key":"B18","doi-asserted-by":"publisher","first-page":"468","DOI":"10.3390\/s25020468","article-title":"Design of a cost-effective ultrasound force sensor and force control system for robotic extra-body ultrasound imaging","volume":"25","author":"Zheng","year":"2025","journal-title":"Sensors"},{"key":"B19","doi-asserted-by":"publisher","first-page":"1495","DOI":"10.1057\/s41599-024-04028-8","article-title":"Patient acceptance of medical service robots in the medical intelligence era: an empirical study based on an extended AI device use acceptance model","volume":"11","author":"Li","year":"","journal-title":"Humanit Soc Sci Commun"},{"key":"B20","doi-asserted-by":"publisher","first-page":"e37952","DOI":"10.2196\/37952","article-title":"Digital patient experience","volume":"24","author":"Wang","year":"2022","journal-title":"Umbrella Systematic Review. J Med Internet Res"},{"key":"B21","doi-asserted-by":"publisher","first-page":"1566","DOI":"10.1056\/NEJMoa2303911","article-title":"Automated insulin delivery in women with pregnancy complicated by type 1 diabetes","volume":"389","author":"Lee","year":"2023","journal-title":"N Engl J Med"},{"key":"B22","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1038\/s41746-025-01709-9","article-title":"A distributional reinforcement learning model for optimal glucose control after cardiac surgery","volume":"8","author":"Desman","year":"2025","journal-title":"npj Digit Med"},{"key":"B23","doi-asserted-by":"publisher","first-page":"7091","DOI":"10.1038\/s41467-025-62538-8","article-title":"Personalized ML-based wearable robot control improves impaired arm function","volume":"16","author":"Arnold","year":"2025","journal-title":"Nat Commun"},{"key":"B24","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1038\/s41528-021-00107-x","article-title":"Advances in healthcare wearable devices","volume":"5","author":"Iqbal","year":"2021","journal-title":"npj Flex Electron"},{"key":"B25","author":"Padmanabha","year":"2025"},{"key":"B26","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1038\/s41746-024-01182-w","article-title":"A systematic review of the impacts of remote patient monitoring (RPM) interventions on safety, adherence, quality-of-life and cost-related outcomes","volume":"7","author":"Tan","year":"2024","journal-title":"npj Digit Med"},{"key":"B27","doi-asserted-by":"publisher","first-page":"24088","DOI":"10.1038\/s41598-025-09727-z","article-title":"Enhancing remote patient monitoring with AI-driven IoMT and cloud computing technologies","volume":"15","author":"Damera","year":"2025","journal-title":"Sci Rep"},{"key":"B28","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1080\/07317115.2022.2156829","article-title":"My precious friend: human-robot interactions in home care for socially isolated older adults","volume":"47","author":"Lee","year":"2024","journal-title":"Clin Gerontol"},{"key":"B29","doi-asserted-by":"publisher","first-page":"e70439","DOI":"10.2196\/70439","article-title":"Responsible design, integration, and use of generative AI in mental health","volume":"12","author":"Asman","year":"2025","journal-title":"JMIR Ment Health"},{"key":"B30","doi-asserted-by":"publisher","first-page":"100320","DOI":"10.1016\/j.invent.2020.100320","article-title":"Social robots as treatment agents: pilot randomized controlled trial to deliver a behavior change intervention","volume":"21","author":"Robinson","year":"2020","journal-title":"Internet Interv"},{"key":"B31","doi-asserted-by":"crossref","first-page":"1235","DOI":"10.1007\/978-3-030-96729-1_57","article-title":"Medical automation and robotics","volume-title":"Springer Handbook of Automation","author":"Wolf","year":"2023"},{"key":"B32","doi-asserted-by":"crossref","DOI":"10.1109\/ICRA57147.2024.10611637","article-title":"Orbit-Surgical: an open-simulation framework for learning surgical augmented dexterity","author":"Yu","year":"2024"},{"key":"B33","volume-title":"World Population Ageing 2020 Highliths: Living Arrangements of Older Persons","year":"2020"},{"key":"B34","doi-asserted-by":"publisher","first-page":"2980","DOI":"10.3390\/ijerph18062980","article-title":"Access to healthcare during COVID-19","volume":"18","author":"N\u00fa\u00f1ez","year":"2021","journal-title":"Int J Environ Res Public Health"},{"key":"B35","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMp2006141","article-title":"Critical supply shortages \u2014 the need for ventilators and personal protective equipment during the COVID-19 pandemic","volume":"382","author":"Ranney","year":"2020","journal-title":"N Engl J Med"},{"key":"B36","doi-asserted-by":"publisher","first-page":"1590","DOI":"10.1109\/ACCESS.2020.3045792","article-title":"Robots under COVID-19 pandemic: a comprehensive survey","volume":"9","author":"Shen","year":"2021","journal-title":"IEEE Access"},{"key":"B37","doi-asserted-by":"publisher","first-page":"2200408","DOI":"10.1002\/aisy.202200408","article-title":"Persistent human\u2013machine interfaces for robotic arm control via gaze and eye direction tracking","volume":"5","author":"Ban","year":"2023","journal-title":"Adv Intell Syst"},{"key":"B38","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1007\/978-3-031-43901-8_13","article-title":"MI-SegNet: mutual information-based US segmentation for unseen domain generalization","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2023","author":"Bi","year":"2023"},{"key":"B39","doi-asserted-by":"publisher","first-page":"8778","DOI":"10.1007\/s00464-023-10322-4","article-title":"Bringing artificial intelligence to the operating room: edge computing for real-time surgical phase recognition","volume":"37","author":"Choksi","year":"","journal-title":"Surg Endosc"},{"key":"B40","doi-asserted-by":"publisher","first-page":"1089062","DOI":"10.3389\/frobt.2023.1089062","article-title":"On the role and opportunities in teamwork design for advanced multi-robot search systems","volume":"10","author":"Francos","year":"2023","journal-title":"Front Robot AI"},{"key":"B41","author":"Xue","year":"2023"},{"key":"B42","doi-asserted-by":"publisher","first-page":"eadt5254","DOI":"10.1126\/scirobotics.adt5254","article-title":"SRT-H: a hierarchical framework for autonomous surgery via language-conditioned imitation learning","volume":"10","author":"Kim","year":"2025","journal-title":"Sci Robot"},{"key":"B43","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1109\/TMRB.2019.2913282","article-title":"Autonomy for surgical robots: concepts and paradigms","volume":"1","author":"Haidegger","year":"2019","journal-title":"IEEE Trans Med Robot Bionics"},{"key":"B44","doi-asserted-by":"publisher","first-page":"eaam8638","DOI":"10.1126\/scirobotics.aam8638","article-title":"Medical robotics\u2014regulatory, ethical, and legal considerations for increasing levels of autonomy","volume":"2","author":"Yang","year":"2017","journal-title":"Sci Robot"},{"key":"B45","doi-asserted-by":"publisher","first-page":"770","DOI":"10.1001\/jamasurg.2018.1512","article-title":"Automated performance metrics and machine learning algorithms to measure surgeon performance and anticipate clinical outcomes in robotic surgery","volume":"153","author":"Hung","year":"2018","journal-title":"JAMA Surg"},{"key":"B46","article-title":"Meta-Reinforcement learning via language instructions","author":"Bing","year":"2022"},{"key":"B47","doi-asserted-by":"publisher","first-page":"2379","DOI":"10.1093\/jamia\/ocae215","article-title":"A review of reinforcement learning for natural language processing and applications in healthcare","volume":"31","author":"Liu","year":"2024","journal-title":"J Am Med Inform Assoc"},{"key":"B48","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1146\/annurev-control-071223-105834","article-title":"Inferring human intent and predicting human action in human\u2013robot collaboration","volume":"7","author":"Hoffman","year":"2024","journal-title":"Annu Rev Control Robot Auton Syst"},{"key":"B49","doi-asserted-by":"publisher","first-page":"4441","DOI":"10.1109\/LRA.2023.3284380","article-title":"Human-in-the-Loop embodied intelligence with interactive simulation environment for surgical robot learning","volume":"8","author":"Long","year":"2023","journal-title":"IEEE Robot Autom Lett"},{"key":"B50","author":"Brodeur","year":"2024"},{"key":"B51","year":"2025"},{"key":"B52","doi-asserted-by":"publisher","first-page":"112","DOI":"10.3390\/robotics13080112","article-title":"The future of intelligent healthcare: a systematic analysis and discussion on the integration and impact of robots using large language models for healthcare","volume":"13","author":"Pashangpour","year":"2024","journal-title":"Robotics"},{"key":"B53","author":"Belcak","year":"2025"},{"key":"B54","year":""},{"key":"B55","doi-asserted-by":"publisher","first-page":"1200576","DOI":"10.3389\/fnins.2023.1200576","article-title":"A touch-free human-robot collaborative surgical navigation robotic system based on hand gesture recognition","volume":"17","author":"Wang","year":"2023","journal-title":"Front Neurosci"},{"key":"B56","doi-asserted-by":"publisher","first-page":"e2534976","DOI":"10.1001\/jamanetworkopen.2025.34976","article-title":"Use of ambient AI scribes to reduce administrative burden and professional burnout","volume":"8","author":"Olson","year":"2025","journal-title":"JAMA Netw Open"},{"key":"B57","doi-asserted-by":"publisher","DOI":"10.1056\/CAT.23.0404","article-title":"Ambient artificial intelligence scribes to alleviate the burden of clinical documentation","volume":"5","author":"Tierney","year":"2024","journal-title":"NEJM Catalyst"},{"key":"B58","doi-asserted-by":"publisher","first-page":"104717","DOI":"10.1016\/j.ijmedinf.2022.104717","article-title":"Improving the user experience of televisits and telemonitoring for heart failure patients in less than 6 months: a methodological approach","volume":"161","author":"Savoldelli","year":"2022","journal-title":"Int J Med Inf"},{"key":"B59","doi-asserted-by":"publisher","first-page":"100577","DOI":"10.1016\/j.smhl.2025.100577","article-title":"Dynamic fog computing for enhanced LLM execution in medical applications","volume":"36","author":"Zagar","year":"2025","journal-title":"Smart Health"},{"key":"B60","doi-asserted-by":"publisher","first-page":"5799","DOI":"10.1109\/OJCOMS.2024.3456549","article-title":"LLM-Based Edge intelligence: a comprehensive survey on architectures, applications, security and trustworthiness","volume":"5","author":"Friha","year":"2024","journal-title":"IEEE Open J Commun Soc"},{"key":"B61","author":"Jegham","year":"2025"},{"key":"B62","article-title":"LLM-Driven Adjustments in serious games: a feasibility analysis","volume-title":"Studies in Health Technology and Informatics","author":"Mostachetti","year":"2025"},{"key":"B63","doi-asserted-by":"publisher","DOI":"10.1056\/AIp2400392","article-title":"Preparing for the widespread adoption of clinic visit recording","volume":"1","author":"Barr","year":"2024","journal-title":"NEJM AI"},{"key":"B64","doi-asserted-by":"publisher","first-page":"1897","DOI":"10.1007\/s11227-020-03325-8","article-title":"A systematic literature review on hardware implementation of artificial intelligence algorithms","volume":"77","author":"Talib","year":"2021","journal-title":"J Supercomput"},{"key":"B65","doi-asserted-by":"publisher","first-page":"61600","DOI":"10.1109\/ACCESS.2023.3285596","article-title":"Artificial intelligence and biosensors in healthcare and its clinical relevance: a review","volume":"11","author":"Qureshi","year":"2023","journal-title":"IEEE Access"},{"key":"B66","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1177\/02783649251346211","article-title":"GRADE: generating realistic and dynamic environments for robotics research with isaac sim","volume":"16","author":"Bonetto","year":"2025","journal-title":"Int J Rob Res"},{"key":"B67","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/j.eng.2023.01.009","article-title":"A reconfigurable data glove for reconstructing physical and virtual grasps","volume":"32","author":"Liu","year":"2024","journal-title":"Engineering"},{"key":"B68","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1038\/s41551-021-00751-8","article-title":"Synthetic data in machine learning for medicine and healthcare","volume":"5","author":"Chen","year":"2021","journal-title":"Nat Biomed Eng"},{"key":"B69","doi-asserted-by":"publisher","first-page":"1749","DOI":"10.3390\/biomedicines11061749","article-title":"Synthesizing electronic health records for predictive models in low-middle-income countries (LMICs)","volume":"11","author":"Ghosheh","year":"2023","journal-title":"Biomedicines"},{"key":"B70","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1038\/s41746-022-00700-y","article-title":"Artificial intelligence for strengthening healthcare systems in low- and middle-income countries: a systematic scoping review","volume":"5","author":"Ciecierski-Holmes","year":"2022","journal-title":"npj Digit Med"},{"key":"B71","doi-asserted-by":"publisher","first-page":"178","DOI":"10.3389\/fpubh.2020.00178","article-title":"Over- and under-sampling approach for extremely imbalanced and small minority data problem in health record analysis","volume":"8","author":"Fujiwara","year":"2020","journal-title":"Front Public Health"},{"key":"B72","year":""},{"key":"B73","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1038\/s41746-024-01085-w","article-title":"Distribution shift detection for the postmarket surveillance of medical AI algorithms: a retrospective simulation study","volume":"7","author":"Koch","year":"2024","journal-title":"npj Digit Med"},{"key":"B74","year":"2025"},{"key":"B75","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1038\/s41746-022-00693-8","article-title":"Protecting procedural care\u2014cybersecurity considerations for robotic surgery","volume":"5","author":"Gordon","year":"2022","journal-title":"npj Digit Med"},{"key":"B76","doi-asserted-by":"publisher","first-page":"102861","DOI":"10.1016\/j.artmed.2024.102861","article-title":"Challenges and strategies for wide-scale artificial intelligence (AI) deployment in healthcare practices: a perspective for healthcare organizations","volume":"151","author":"Esmaeilzadeh","year":"2024","journal-title":"Artif Intell Med"}],"container-title":["Frontiers in Digital Health"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fdgth.2026.1914012\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T05:36:02Z","timestamp":1788240962000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fdgth.2026.1914012\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,1]]},"references-count":76,"alternative-id":["10.3389\/fdgth.2026.1914012"],"URL":"https:\/\/doi.org\/10.3389\/fdgth.2026.1914012","relation":{},"ISSN":["2673-253X"],"issn-type":[{"value":"2673-253X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,1]]},"article-number":"1914012"}}