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| 치료약물모니터링 (Therapeutic Drug Monitoring, TDM)× | 베이즈 추론× | |
|---|---|---|
| 분야≠ | 계량약리학 | 통계학 |
| 계열≠ | Regression model | Bayesian methods |
| 기원 연도≠ | 1988 | 1763 |
| 창시자≠ | Reynold Spector et al. | Thomas Bayes; Pierre-Simon Laplace |
| 유형≠ | Clinical measurement and dose-optimization framework | Probabilistic inference paradigm |
| 원전≠ | Spector, R., Park, G. D., Johnson, G. F., & Vesell, E. S. (1988). Therapeutic drug monitoring. Clinical Pharmacology & Therapeutics, 43(4), 345–353. DOI ↗ | Bayes, T. (1763). An essay towards solving a problem in the doctrine of chances. Philosophical Transactions of the Royal Society of London, 53, 370–418. link ↗ |
| 별칭≠ | Drug Level Monitoring, Serum Drug Level Monitoring, Clinical Pharmacokinetic Monitoring, İlaç Düzeyi İzlemi | Bayes inference, Bayesian statistics, Bayesian updating, posterior inference |
| 관련 | 3 | 3 |
| 요약≠ | Therapeutic Drug Monitoring (TDM) is a clinical pharmacokinetic practice in which drug concentrations are measured in a patient's blood to guide individualized dosing. It applies principally to drugs with narrow therapeutic windows—where the margin between efficacy and toxicity is small—such as aminoglycosides, vancomycin, cyclosporine, and antiepileptics. Developed as a formal discipline in the 1980s, TDM integrates measured concentrations with pharmacokinetic modeling to calculate patient-specific dose regimens. | Bayesian inference is a statistical paradigm in which probability represents degrees of belief rather than long-run frequencies. It encodes prior knowledge about parameters in a prior distribution, combines that prior with the likelihood of observed data via Bayes' theorem, and produces a posterior distribution that quantifies updated uncertainty. The foundational theorem was published posthumously by Thomas Bayes in 1763 and subsequently systematized by Pierre-Simon Laplace in his 1812 Théorie analytique des probabilités. |
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