Collection 

Digital twins for precision health

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A digital twin for precision health is a set of virtual information constructs that mimics the structure, context, and behavior of a human body or health systems (or system-of-systems), is dynamically and continuously updated with data from its physical twin, has a predictive capability, its correctness can be verified and informs decisions that realize value and resemble actionable information to guide health and wellness care delivery. The bidirectional interaction between the virtual and the physical is central to the digital twin. The bidirectional flow of information from the human health system to the computational model affects a twin that remains tightly coupled with the human health system leading to more effective identification of risk factors in the presence of current or future behavior, and/or adverse events. 

[definition adopted from 1. National Academies of Sciences, Engineering, and Medicine. 2023. Foundational Research Gaps and Future Directions for Digital Twins. Washington, DC: The National Academies Press. and 2. AIAA (American Institute of Aeronautics and Astronautics). Digital Engineering Integration Committee. 2020. “Digital Twin: Definition & Value.” AIAA and AIA Position Paper, AIAA, Reston, VA.)

Potential topics could include: 
 

  1. Foundations of digital twins for precision health
  2. Novel sensors and models for digital twins
  3. Artificial intelligence (AI) and digital twins
  4. Digital twins for health, including but not limited to: 
  • Cardiovascular Health
  • Mental and Behavioral Health
  • Neurological Disorders and Stroke Prevention
  • Infectious Diseases
  • Diabetes

This Collection supports and amplifies research related to SDG 3: Good health and wellbeing.

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A woman with her brain being scanned looks at her digital twin

Editors

Peter Hunter, PhD, University of Auckland, Auckland, New Zealand

Distinguished Professor Peter Hunter, earned his engineering degree in 1971 from the University of Auckland, New Zealand, and completed a Master of Engineering and a DPhil (PhD) in Physiology at the University of Oxford in 1975. Pioneering the development of the first 'physiome' model, he explores the human body's intricacies, emphasizing computational algorithms with a biophysically grounded approach. Currently, Professor Hunter serves as Co-Chair of the Physiome Committee at the International Union of Physiological Sciences, guiding the Physiome Project's efforts to establish model and data encoding standards. Alongside founding the Auckland Bioengineering Institute, he holds leadership roles at the University of Auckland and Oxford University, contributing expertise to global scientific advisory boards. His distinguished career includes being a Fellow of the Royal Society (London and NZ), the World Council for Biomechanics, the American Institute for Medical and Biological Engineering, and the International Academy of Medical & Biological Engineering. Notably, he received the NZ Order of Merit in 2010 and the Rutherford Medal in 2009, acknowledging his significant contributions to science.

Roozbeh Jafari, PhD, Texas A&M University, TX, USA

Roozbeh Jafari is the Tim and Amy Leach Professor at Texas A&M University. He holds appointments in the School of Engineering Medicine in Houston and the College of Engineering in College Station. Spanning Electrical and Computer Engineering, Biomedical Engineering, Computer Science, and Engineering departments, he earned his Ph.D. in Computer Science from UCLA and completed a postdoctoral fellowship at UC Berkeley. Specializing in wearable computer design and signal processing, he has secured over $89M for research, with $25M directed to his lab from sources such as NSF, NIH, DoD, DARPA, and industry leaders like Texas Instruments and Samsung. Authoring 200+ papers, he has chaired conferences, is an Associate Editor for npj Digital Medicine, and serves on the Editorial Board of several other journals. He is currently the elected Chair of the IEEE Wearable Biomedical Sensors and Systems Technical Committee, as well as the IEEE Applied Signal Processing Technical Committee. He is a fellow of the American Institute for Medical and Biological Engineering (AIMBE). Professor Jarafi’s contributions extend to pivotal roles in NIH study sections, reflecting his significant influence in the realm of wearable technology and biomedical research.