AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare
Sitah Alharthi · 2025
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Description
Alharthi maps a new kind of medical double: the in silico twin. Such a twin is a computer replica of one patient, fed by that person's data and updated in real time. It blends body-based models with AI so doctors can simulate treatments before trying them. The review sets the twin apart from cousins like digital twins and virtual patients.
Alharthi surveys the machinery underneath: learning algorithms, multi-scale body models, data plumbing, and cloud computing. Uses span the care journey, from early warning to drug choice. The review adds a taxonomy of twin designs, a checklist for trusting a model's output, and a blueprint for putting twins to work in real clinics.
Catalog record
| CREATOR | Sitah Alharthi |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 172 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |