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Exploring the Application of Digital Twin Technology in Investigating the Relationship Between Contraceptive Use and Breast Cancer Incidence
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Author(s): Banashree Bondhopadhyay (Amity University, Noida, India), Hina Bansal (Amity University, Noida, India), Navya Aggarwal (Amity University, Noida, India)and Aastha Tanwar (Amity University, Noida, India)
Copyright: 2024
Pages: 27
Source title:
Exploring the Advancements and Future Directions of Digital Twins in Healthcare 6.0
Source Author(s)/Editor(s): Archi Dubey (The ICFAI University, India), C. Kishor Kumar Reddy (Stanley College of Engineering and Technology for Women, India), Srinath Doss (Botho University, Botswana)and Marlia Mohd Hanafiah (Universiti Kebangsaan Malaysia, Malaysia)
DOI: 10.4018/979-8-3693-5893-1.ch018
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Abstract
Contraception has long been scrutinized for its impact on women's health, particularly concerning breast cancer risk. The study explores the analysis of digital twin (DT) tools and technologies. Leveraging DTs in healthcare, by integrating medical data and employing machine learning, predictive models can be developed, representing individual patients, assessing the influence of contraceptive methods on breast cancer risk. They may aid in finding associations between specific contraceptive methods and breast cancer incidence. DTs pave the way for the development of smart IUDs/IUSs, which can be termed as “cyclic-release” devices/systems, that could tailor progesterone release based on the phases of the female ovulation cycle, potentially enhancing effectiveness and minimizing side effects. Moreover, real-time monitoring in DTs offer insights into dynamic changes in risk profiles. Thus, DTs may help in personalized contraceptive counselling and preventive strategies, fostering better-informed decision-making and improved health outcomes for women worldwide.
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