Software
We provide services to help researchers develop statistical software packages and interactive web applications for data analysis and visualization.
PheCAP: High-throughput phenotyping with electronic medical record data using a common semi-supervised approach. This package implements surrogate-assisted feature extraction (SAFE) and common machine learning approaches to train and validate phenotyping models.
PheNorm: The algorithm combines the most predictive variable, such as count of the main International Classification of Diseases (ICD) codes, and other Electronic Health Record (EHR) features (e.g. health utilization and processed clinical note data), to obtain a score for accurate risk prediction and disease classification.
KESER: This packages implements the Knowledge Extraction via Sparse Embedding Regression (KESER) algorithm. We provide functions to use large scale code embeddings to facilitate effective feature selection and knowledge discovery with EHR data.