69 citations
6 papers
Efficient Learning of Optimal Individualized Treatment Rules for Heteroscedastic or Misspecified Treatment-Free Effect Models
Weibin Mo, Yufeng Liu
Recent development in data-driven decision science has seen great advances in individualized decision making. Given data with individual covariates, treatment assignments and outco…
Projected -SNE for batch correction
Emanuele Aliverti, Jeff Tilson, Dayne Filer +6
Biomedical research often produces high-dimensional data confounded by batch effects such as systematic experimental variations, different protocols and subject identifiers. Withou…
Multiple Instance Learning for Heterogeneous Images: Training a CNN for Histopathology
Heather D. Couture, J. S. Marron, Charles M. Perou +2
Multiple instance (MI) learning with a convolutional neural network enables end-to-end training in the presence of weak image-level labels. We propose a new method for aggregating…
Modeling Between-Study Heterogeneity for Improved Reproducibility in Gene Signature Selection and Clinical Prediction
Naim U. Rashid, Quefeng Li, Jen Jen Yeh +1
In the genomic era, the identification of gene signatures associated with disease is of significant interest. Such signatures are often used to predict clinical outcomes in new pat…
Statistical Significance of Clustering using Soft Thresholding
Hanwen Huang, Yufeng Liu, Ming Yuan +1
Clustering methods have led to a number of important discoveries in bioinformatics and beyond. A major challenge in their use is determining which clusters represent important unde…
A quantitative system for discriminating induced pluripotent stem cells, embryonic stem cells and somatic cells
Anyou Wang
Embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) derived from somatic cells (SCs) provide promising resources for regenerative medicine and medical research,…