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DC Field | Value | Language |
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dc.contributor.author | Smokovski, I. | - |
dc.contributor.author | Steinle, N. | - |
dc.contributor.author | Behnke, A. | - |
dc.contributor.author | Bhaskar, S. M. M. | - |
dc.contributor.author | Grech, G. | - |
dc.contributor.author | Richter, K. | - |
dc.contributor.author | Niklewski, G. | - |
dc.contributor.author | Birkenbihl, C. | - |
dc.contributor.author | Parini, P. | - |
dc.contributor.author | Andrews, R. J. | - |
dc.contributor.author | Bauchner, H. | - |
dc.contributor.author | Golubnitschaja, O. | - |
dc.date.accessioned | 2024-06-03T03:25:41Z | - |
dc.date.available | 2024-06-03T03:25:41Z | - |
dc.date.issued | 2024 | - |
dc.identifier.issn | 18785077 (ISSN) | - |
dc.identifier.uri | https://swslhd.intersearch.com.au/swslhdjspui/handle/1/12743 | - |
dc.description.abstract | Non-communicable chronic diseases (NCDs) have become a major global health concern. They constitute the leading cause of disabilities, increased morbidity, mortality, and socio-economic disasters worldwide. Medical condition-specific digital biomarker (DB) panels have emerged as valuable tools to manage NCDs. DBs refer to the measurable and quantifiable physiological, behavioral, and environmental parameters collected for an individual through innovative digital health technologies, including wearables, smart devices, and medical sensors. By leveraging digital technologies, healthcare providers can gather real-time data and insights, enabling them to deliver more proactive and tailored interventions to individuals at risk and patients diagnosed with NCDs. Continuous monitoring of relevant health parameters through wearable devices or smartphone applications allows patients and clinicians to track the progression of NCDs in real time. With the introduction of digital biomarker monitoring (DBM), a new quality of primary and secondary healthcare is being offered with promising opportunities for health risk assessment and protection against health-to-disease transitions in vulnerable sub-populations. DBM enables healthcare providers to take the most cost-effective targeted preventive measures, to detect disease developments early, and to introduce personalized interventions. Consequently, they benefit the quality of life (QoL) of affected individuals, healthcare economy, and society at large. DBM is instrumental for the paradigm shift from reactive medical services to 3PM approach promoted by the European Association for Predictive, Preventive, and Personalized Medicine (EPMA) involving 3PM experts from 55 countries worldwide. This position manuscript consolidates multi-professional expertise in the area, demonstrating clinically relevant examples and providing the roadmap for implementing 3PM concepts facilitated through DBs. © The Author(s) 2024. | - |
dc.publisher | Springer Science and Business Media Deutschland GmbH | - |
dc.subject | Artificial intelligence Cancer Cardiovascular diseases Chronic obstructive pulmonary disease Diabetes Digital biomarkers Health economy and policy Health protection Health risk assessment Health-to-disease transition Innovative ecosystem Machine learning Non-communicable chronic disease Perinatal asphyxia PPPM�/�3PM Predictive�Preventive Personalized Medicine Primary and secondary care Sleep disorders Wearable point-of-care devices | - |
dc.title | Digital biomarkers: 3PM approach revolutionizing chronic disease management ? EPMA 2024 position | - |
dc.type | Journal Article | - |
dc.contributor.swslhdauthor | Bhaskar, Sonu M. | - |
dc.description.affiliates | University Clinic of Endocrinology, Diabetes and Metabolic Disorders, Skopje, North Macedonia Faculty of Medical Sciences, University Goce Delcev, Stip, North Macedonia Veteran Affairs Capitol Health Care Network, Linthicum, MD, United States University of Maryland School of Medicine, Baltimore, MD, United States Endocrinology Section, Carilion Clinic, Roanoke, VA, United States Virginia Tech Carilion School of Medicine, Roanoke, VA, United States Department of Neurology, Division of Cerebrovascular Medicine and Neurology, National Cerebral and Cardiovascular Centre (NCVC), Osaka, Suita, Japan Department of Neurology & amp; Neurophysiology, Liverpool Hospital, Ingham Institute for Applied Medical Research and South Western Sydney Local Health District, Sydney, NSW, Australia NSW Brain Clot Bank, Global Health Neurology Lab & amp; NSW Health Pathology, Sydney, NSW, Australia Department of Pathology, Faculty of Medicine & amp; Surgery, University of Malta, Msida, Malta CuraMed Tagesklinik N�rnberg GmbH, Nuremberg, Germany Technische Hochschule N�rnberg GSO, Nuremberg, Germany University Clinic for Psychiatry and Psychotherapy, Paracelsus Medical University, Nuremberg, Germany Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States Cardio Metabolic Unit, Department of Medicine Huddinge, and Department of Laboratory Medicine, Karolinska Institute, and Medicine Unit of Endocrinology, Theme Inflammation and Ageing, Karolinska University Hospital, Stockholm, Sweden Nanotechnology & amp; Smart Systems Groups, NASA Ames Research Center, Aerospace Medical Association, Silicon Valley, CA, United States Boston University Chobanian & amp; Avedisian School of Medicine, Boston, MA, United States Predictive, Preventive and Personalized (3P) Medicine, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universit�t Bonn, Bonn, Germany | - |
dc.identifier.doi | 10.1007/s13167-024-00364-6 | - |
dc.identifier.department | Liverpool Hospital, Department of Neurology and Neurophysiology | - |
dc.type.studyortrial | Article | - |
dc.identifier.journaltitle | EPMA Journal | - |
Appears in Collections: | Liverpool Hospital South Western Sydney Local Health District |
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