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DC Field | Value | Language |
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dc.contributor.author | Gnanamalar R, Hepziba | - |
dc.date.accessioned | 2024-10-21T11:11:43Z | - |
dc.date.available | 2024-10-21T11:11:43Z | - |
dc.date.issued | 2024-01-01 | - |
dc.identifier.isbn | 978-303158523-4 | - |
dc.identifier.uri | https://link.springer.com/chapter/10.1007/978-3-031-58523-4_10 | - |
dc.description.abstract | In recent years, the concept of the human digital twin has emerged as a promising approach to revolutionize healthcare and unlock the full potential of precision medicine. By creating a virtual replica of an individual’s biological, physiological, and behavioral characteristics, a human digital twin can be used to develop personalized treatment plans, improve disease prevention, and discover genetics that contribute to health and disease. A human digital twin enables a deeper understanding of the complex interplay between environmental and lifestyle factors. It is used in various industries, such as aerospace and automotive, to optimize product design, predict performance, and improve maintenance. However, the application of this concept to human health is still in its early stages. Significant challenges remain to be overcome, and significant gains could be realized. One of the key benefits of the human digital twin is the ability to integrate and analyze large numbers of data from various sources, such as electronic medical records, genomic information, wearable devices, and even social media. A comprehensive view of human health can identify early warning signs of disease, enabling timely intervention and prevention strategies. For example, digital twins can be used to predict an individual’s risk of developing diabetes on the basis of their genetic makeup, lifestyle, and environmental factors, allowing healthcare providers to tailor diet and exercise regimens to reduce that risk. Plans can be recommended. The human digital twin could unlock the full potential of precision medicine and transform medicine as we know it. Digital twins provide comprehensive and dynamic representations of an individual’s health status to improve patient outcomes, provide personalized prevention and treatment, and broaden our understanding of the complex factors that influence health and disease. Strategies can be formulated. However, realizing these benefits will require overcoming significant technical, ethical, and regulatory challenges and fostering collaboration among researchers, healthcare providers, patients, and policymakers. The successful integration of the human digital twin into healthcare will undoubtedly pave the way for a new era of personalized, data-driven medicine that improves individual and collective health. This chapter consists of seven sections. Section “Introduction” discusses the history, evolution, process, advantages, and disadvantages of human digital twin technologies. Section “HDT Process with Various Recent Technologies” deliberates about the integration of various recent technologies with human digital twin (HDTs). A conceptual paradigm for HDTs is described in section “Conceptual Paradigm for DT and HDT”. An HDT and a human being are compared in section “Human Digital Twin Technology and Human Beings”. The different types of wearable technologies featuring HDTs are categorized in section “Wearable Devices and HDTs”. Section “Development of Human Digital Twins in Healthcare” provides information on the development of HDTs in healthcare. Finally, section “Conclusion” concludes all other sections. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Springer Nature | en_US |
dc.title | HUMAN DIGITAL TWIN PROCESSES AND THEIR FUTURE | en_US |
dc.type | Book chapter | en_US |
Appears in Collections: | 3.Book Chapter (18) |
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File | Description | Size | Format | |
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HUMAN DIGITAL TWIN PROCESSES AND THEIR FUTURE.docx | 608.84 kB | Microsoft Word XML | View/Open |
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