28 citations · 45 across the 8 of their papers we have counts for
7 papers · 1 filter
Bayesian Multi-Arm De-Intensification Designs
Steffen Ventz, Lorenzo Trippa
In recent years new cancer treatments improved survival in multiple histologies. Some of these therapeutics, and in particular treatment combinations, are often associated with sev…
Combining Breast Cancer Risk Prediction Models
Zoe Guan, Theodore Huang, Anne Marie McCarthy +6
Accurate risk stratification is key to reducing cancer morbidity through targeted screening and preventative interventions. Numerous breast cancer risk prediction models have been…
Integration of Survival Data from Multiple Studies
Steffen Ventz, Rahul Mazumder, Lorenzo Trippa
We introduce a statistical procedure that integrates survival data from multiple biomedical studies, to improve the accuracy of predictions of survival or other events, based on in…
Bayesian Uncertainty Directed Trial Designs
Steffen Ventz, Matteo Cellamare, Sergio Bacallado +1
Most Bayesian response-adaptive designs unbalance randomization rates towards the most promising arms with the goal of increasing the number of positive treatment outcomes during t…
Bayesian Multi-study Factor Analysis for High-throughput Biological Data
Roberta De Vito, Ruggero Bellio, Lorenzo Trippa +1
This paper presents a new modeling strategy for joint unsupervised analysis of multiple high-throughput biological studies. As in Multi-study Factor Analysis, our goals are to iden…
Bayesian nonparametric cross-study validation of prediction methods
Lorenzo Trippa, Levi Waldron, Curtis Huttenhower +1
We consider comparisons of statistical learning algorithms using multiple data sets, via leave-one-in cross-study validation: each of the algorithms is trained on one data set; the…