BACKGROUND: Modern causal inference methods allow machine learning to be used to weaken parametric modeling assumptions. However, the use of machine learning may result in complications for inference. Doubly robust cross-fit estimators have been prop...
Data science skills are increasingly needed by informatics nurses and nurse scientists, but techniques such as machine learning can be daunting for those with clinical, rather than computer science or technical, backgrounds. With the increasing quant...
Artificial intelligence is an exciting and growing field in medicine to assist in the proper diagnosis of patients. Although the use of artificial intelligence in orthopedics is currently limited, its utility in other fields has been extremely valuab...
MOTIVATION: Procedures for structural modeling of protein-protein complexes (protein docking) produce a number of models which need to be further analyzed and scored. Scoring can be based on independently determined constraints on the structure of th...
BACKGROUND: Allogeneic hematopoietic cell transplantation (allo-HCT) is a curative treatment option for malignant hematological disorders. Transplant clinicians estimate patient-specific prognosis empirically in clinical practice based on previous st...
Microcapsules, consisting of a liquid droplet enclosed by a viscoelastic membrane, have a wide range of biomedical and pharmaceutical applications and also serve as a popular mechanical model for biological cells. In this study, we develop a novel hi...
N6-methyladenosine (m6A) is the most pervasive modification in eukaryotic mRNAs. Numerous biological processes are regulated by this critical post-transcriptional mark, such as gene expression, RNA stability, RNA structure and translation. Recently, ...
MOTIVATION: Many researchers with domain expertise are unable to easily apply machine learning (ML) to their bioinformatics data due to a lack of ML and/or coding expertise. Methods that have been proposed thus far to automate ML mostly require progr...
SUMMARY: treeheatr is an R package for creating interpretable decision tree visualizations with the data represented as a heatmap at the tree's leaf nodes. The integrated presentation of the tree structure along with an overview of the data efficient...
BACKGROUND: Aneurysmal subarachnoid hemorrhage (aSAH) is associated with a high mortality and poor neurologic outcomes. The biologic underpinnings of the morbidity and mortality associated with aSAH remain poorly understood.
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