Digital Twins in Healthcare: Methodological Challenges and Opportunities
| Type | review |
|---|---|
| Area | Digital Twin |
| Published(YearMonth) | 2310 |
| Source | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10608065/ |
| Tag | newsletter |
| Checkbox | |
| Date(of entry) |
This review delves into the role of digital twins in healthcare, showcasing their potential in enhancing patient monitoring, diagnosis, and personalized treatment strategies. By integrating diverse data sources, including physiological measurements and omics data, digital twins offer a detailed virtual representation of individual patients. Despite the significant progress, challenges such as data standardization and the need for advanced computational power persist. Overcoming these hurdles is crucial for fully realizing the benefits of digital twins in personalized medicine, promising a future where healthcare is more predictive, personalized, and effective.