J. Alexander

POR_A_214412 67..76

R. Edwards, B. Parsons, J. Alexander, 2019 .

Integrating Machine Learning With Microsimulation to Classify Hypothetical, Novel Patients for Predicting Pregabalin Treatment Response Based on Observational and Randomized Data in Patients With Painful Diabetic Peripheral Neuropathy

R. Edwards, B. Parsons, J. Alexander, 2019, Pragmatic and observational research.

Integrating data from randomized controlled trials and observational studies to predict the response to pregabalin in patients with painful diabetic peripheral neuropathy

R. Edwards, A. Savoldelli, B. Parsons, 2017, BMC Medical Research Methodology.

Predicting Responses to Pregabalin for Painful Diabetic Peripheral Neuropathy Based on Trajectory-Focused Patient Profiles Derived from the First 4 Weeks of Treatment

R. Edwards, B. Parsons, J. Alexander, 2018, Advances in Therapy.

Using time series analysis approaches for improved prediction of pain outcomes in subgroups of patients with painful diabetic peripheral neuropathy

R. Edwards, A. Savoldelli, B. Parsons, 2018, PloS one.

Assessing the Value of Time Series Real-World and Clinical Trial Data vs. Baseline-Only Data in Predicting Responses to Pregabalin Therapy for Patients with Painful Diabetic Peripheral Neuropathy

R. Edwards, A. Savoldelli, B. Parsons, 2019, Clinical Drug Investigation.

Correction: Using time series analysis approaches for improved prediction of pain outcomes in subgroups of patients with painful diabetic peripheral neuropathy

R. Edwards, A. Savoldelli, B. Parsons, 2018, PloS one.

Dose Titration of Pregabalin in Patients with Painful Diabetic Peripheral Neuropathy: Simulation Based on Observational Study Patients Enriched with Data from Randomized Studies

R. Edwards, B. Parsons, J. Alexander, 2018, Advances in Therapy.