PUBLICATIONs

THE LATEST PUBLICATIONS

Machine Learning Methodology Identifies Predictors of a Cardiovascular Composite Measure Among Severe Peripheral Artery Disease Patients

Using Clinical Trial and Real World Data to Bridge Efficacy to Effectiveness of Fingolimod in Multiple Sclerosis Patients

Large-scale identification of clinical and genetic predictors of motor progression in patients with newly diagnosed Parkinson’s disease: a longitudinal cohort study and validation

A Bayesian mathematical model of motor and cognitive outcomes in Parkinson’s disease

Prediction of Hypoglycemia Risk Among Patients with Type 2 Diabetes (T2D) Using an Ensemble-Based, Hypothesis-Free Procedure

Machine Learning Methodology Predicts Comorbidities are Associated With Increased Total Healthcare Costs Among Patients With Severe Peripheral Artery Disease

Bayesian network inference modeling identifies TRIB1 as a novel regulator of cell cycle progression and survival in cancer cells

Bayesian Network Models of Multiple Myeloma: Drivers of High Risk and Durable Response

Treatment Patterns Among Schizophrenia Patients Receiving Paliperidone Palmitate or Atypical Oral Antipsychotics in Community Behavioral Health Organizations

Data-Driven Reconstruction and Simulation of Transcriptional Regulatory Networks in the Htt Allelic Series