An overview of the use of digital twins in the field of health
Code: G-1374
Authors: لیلا شکری زاده آرانی, Parisa Yousefi Konjdar * ℗
Schedule: Not Scheduled!
Tag: Clinical Decision Support System
Download: Download Poster
Abstract:
Abstract
Background and aims: In the digital age, new technologies are rapidly changing and transforming various industries. One of these advanced technologies is Digital Twins, which act as a virtual copy of physical systems. Digital twins enable the simulation, prediction, and optimization of physical systems using real-time data and advanced computational models. In the healthcare sector, this technology has great potential to improve the quality of medical care, personalize treatments, and reduce costs. This review article examines the applications of digital twins in the healthcare sector. Method: This study was conducted using a systematic review method. To collect information, reputable scientific databases including PubMed, IEEE Explore, Science Direct, and Google Scholar were searched. Keywords used included "Digital Twins in Healthcare", "Medical Digital Twins", "Healthcare Simulation," and "Personalized Medicine". Articles published between 2018 and 2024 were reviewed, and finally, 45 relevant articles were selected. Results: 1.Patient Simulation: Digital twins enable the creation of virtual models of patients. These models use clinical, genetic, and lifestyle data to help doctors provide personalized treatments. 2.Disease Prediction: Using digital twins, it is possible to predict the progression of chronic diseases such as diabetes, heart disease, and cancer and take preventive measures. 3.Surgery Optimization: In complex surgeries, digital twins allow surgeons to simulate different scenarios before surgery and choose the best surgical method. 4.Hospital Management: Digital twins can be used to manage hospital resources such as hospital beds, medical equipment, and human resources. 5.Pharmaceutical research: In the pharmaceutical industry, digital twins help researchers test the effects of drugs on virtual models of humans, accelerating the drug development process. Conclusion: As an emerging technology, digital twins have great potential to transform the healthcare sector. By providing accurate virtual models of patients and healthcare systems, this technology enables personalized treatments, disease prediction, and medical process optimization. However, challenges such as data security issues, high implementation costs, and the need for advanced infrastructure still exist that need to be addressed. In the future, as technology advances and costs decrease, digital twins are expected to become an integral part of healthcare systems.
Keywords
Digital Twins, Digital Health, Medical Simulation
