Development of Digital Twins in Medicine: Ai-driven Patient Simulations for Optimizing Endocrine Disorder Therapies
Year: 2024
Type: article
Abstract: This paper explores the potential of digital twins in medicine, focusing on optimizing therapies for endocrine disorders, such as diabetes and thyroid diseases. Digital twins, which integrate patient data and artificial intelligence algorithms, enable therapy outcome simulations and therapy personalization. A systematic review and meta-analysis demonstrated that digital twins provide high simulation accuracy (92%) and reduce adverse effects by 35%. Furthermore, the integration of wearable devices and genetic data enhances therapy outcome predictions. Key challenges include data privacy protection, technology standardization, and ethical considerations. These findings highlight the significant potential of digital twins to advance personalized medicine, emphasizing the need for further research to ensure broader application in practice.
Authors: Milić, Marko Kimi, Sinanović, Šćepan
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W6967931829
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