Bayesian Dose Optimization
Bayesian Dose Optimization is a Bayesian inference-based clinical decision-support method that integrates patient-specific pharmacokinetic data with prior population estimates to dynamically individualize drug dosage regimens for optimized therapeutic outcomes.
56
Publications
2.5K
Citations
244
Authors
119
Institutions
Publications per year
2017–2026
17
Variants
Bayesian Individualized Dosing
56
R. Brigg Turner, Kyle Kojiro, Emily A. Shephard et al. · Pharmacotherapy The Journal of Human Pharmacology and Drug Therapy · 2018 · 130 citations
Two‐Dimensional Dose Finding in Discrete Dose Space
Kai Wang, Anastasia Ivanova · Biometrics · 2005 · 122 citations
1–5 of 56
244
The University of Texas MD Anderson Cancer Center, United States
7 publications · 436 citations
7
h-index
The University of Texas MD Anderson Cancer Center, United States
7 publications · 330 citations
7
h-index
4
h-index
The University of Texas MD Anderson Cancer Center, United States
4 publications · 233 citations
4
h-index
3
h-index
1–5 of 244
119
The University of Texas MD Anderson Cancer Center
Houston, United States
15 h-index
37 publications
1.6K citations
University of Southern California
Los Angeles, United States
4 h-index
10 publications
734 citations

Université de Limoges
Limoges, France
3 h-index
17 publications
478 citations
Louisiana State University
Baton Rouge, United States
3 h-index
3 publications
155 citations
The University of Texas Health Science Center at Houston
Houston, United States
3 h-index
3 publications
216 citations
University of California, Santa Cruz
Santa Cruz, United States
3 h-index
3 publications
97 citations
Inserm
Paris, France
3 h-index
13 publications
406 citations
Case Western Reserve University
Cleveland, United States
2 h-index
4 publications
114 citations
1–8 of 119
6 publications · 266 citations
6
h-index
4 publications · 188 citations
4
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4 publications · 170 citations
4
h-index
3 publications · 267 citations
3
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3 publications · 61 citations
3
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