PUBLICATIONs

THE LATEST PUBLICATIONS

Machine-Learning Enabled Identification of Markers of Huntington’s Disease Progression

Causal modeling of CALGB 80405 (Alliance) identifies network drivers of metastatic colorectal cancer (mCRC)

Accurate Prediction of Clinical Disease Progression in Patients With Advanced Fibrosis Due to NASH using a Bayesian Machine Learning Approach

Machine learning approach to personalized medicine in breast cancer patients: development of data-driven, personalized, causal modeling through identification and understanding of optimal treatments for predicting better disease outcomes

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

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 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