Artificial Intelligence for Precision Antiarrhythmic Drug Therapy in Atrial Fibrillation: From Recurrence Prediction to Comparative Treatment Selection
Alina Scridon, Vasile-Bogdan Halațiu, Dan-Alexandru Cozac · 2026
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Description
Alina Scridon, Vasile-Bogdan Halatiu, and Dan-Alexandru Cozac review artificial intelligence for rhythm drug choice in a 2026 paper. Drugs that control heart rhythm help many atrial fibrillation patients, but benefit varies and side effects are common. Doctors now pick drugs mostly by ruling out unsafe ones, not by predicting which will work best for a given person.
AI tools could merge records, heart traces, scans, wearable data, and gene profiles to forecast benefit and harm, the authors write. Early models already predict drug driven QT prolongation and risky trace patterns from records. Digital twin hearts may one day test drugs in silico first. Safety watch over time is also covered.
Catalog record
| CREATOR | Alina Scridon, Vasile-Bogdan Halațiu, Dan-Alexandru Cozac |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 105 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |