The use of Digital Twins (DTs) or the digital replicas of physical entities has provided benefits to several industry sectors, most notably manufacturing. To date, the application of DTs in the healthcare sector has been minimal, however. But, as pressure increases for more precise and personalized treatments, it behooves us to investigate the potential for DTs in the healthcare context. As a proof-of-concept demonstration prior to working with real patients, we attempt in this paper, to explore the potential for creating and using DTs. We do this in a synthetic environment at this stage, making use of data that is all computer-generated. DTs of synthetic present patients are created making use of data of synthetic past patients. In the real world, the clinical objective for creating such DTs of real patients would be to enable enhanced real-time clinical decision support to enable more precise and personalized care. The objective of the numerical experiment reported in this paper, is to envisage the possibilities and challenges of such an approach. We attempt to better understand the strengths and weaknesses of applying DTs in the healthcare context to support more precise and personalized treatments.
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http://dx.doi.org/10.3233/SHTI230961 | DOI Listing |
J Am Soc Nephrol
January 2025
Barbara T Murphy Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
J Epidemiol Glob Health
January 2025
Department of Internal Medicine, National Taiwan University Hospital and College of Medicine, National Taiwan University, No.7, Chung Shan S. Rd., Zhongzheng District, Taipei City, 100225, Taiwan.
Background: Lipids are known to be involved in carcinogenesis, but the associations between lipid profiles and different lung cancer histological classifications remain unknown.
Methods: Individuals who participated in national adult health surveillance from 2012 to 2018 were included. For patients who developed lung cancer during follow-up, a 1:2 control group of nonlung cancer participants was selected after matching.
Hum Vaccin Immunother
December 2025
Key Laboratory of Epigenetics and Oncology, The Research Center for Preclinical Medicine, Southwest Medical University, Luzhou, Sichuan, China.
Although neo-antigen mRNA vaccines are promising for personalized cancer therapy, their effectiveness is often limited by the immunosuppressive tumor microenvironment (TME). The adenosine AA receptor (AAR) inhibits dendritic cell (DC) function and weakens antitumor T cell responses through hypoxia-driven mechanisms within the TME. This review explores a novel strategy combining neo-antigen mRNA vaccines with AAR antagonists (AARi).
View Article and Find Full Text PDFCochrane Database Syst Rev
January 2025
Cornell Joan Klein Jacobs Center for Precision Nutrition and Health, Cornell University, Ithaca, NY, USA.
Background: Precision nutrition-based methods develop tailored interventions and/or recommendations accounting for determinants of intra- and inter-individual variation in response to the same diet, compared to current 'one-size-fits-all' population-level approaches. Determinants may include genetics, current dietary habits and eating patterns, circadian rhythms, health status, gut microbiome, socioeconomic and psychosocial characteristics, and physical activity. In this systematic review, we examined the evidence base for the effect of interventions based on precision nutrition approaches on overweight and obesity in children and adolescents to help inform future research and global guidelines.
View Article and Find Full Text PDFNano Lett
January 2025
Key Laboratory of Clinical Laboratory Diagnostics (Chinese Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing 400016, P. R. China.
Logical analysis of multiple-miRNA expression information and immediate output of diagnostic results facilitates early cancer detection. In this work, we constructed an isothermal molecular classifier capable of performing computations on multiple miRNAs and directly providing diagnosis results. First, we developed linear-after-the-exponential rolling circle amplification (LATE-RCA), a nearly linear isothermal amplification that does not destroy the original quantitative information about miRNAs.
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