Machine Learning for Pharma using Random Forest, Part II

Introduction to Machine Learning with Random Forest (Pharma/Genetics)


To pick up where we left off last blog post, we discussed the potential of predictive analytics in the genetics of cancer. I aim to achieve this by using the aforementioned Random Forest classification algorithm.

(more…)

Getting the Most Out of Longitudinal Patient Data

Anonymous patient-level data (APLD) is data collected in real time from an individual patient. There has been an increasing interest in patient-level data, as researchers, healthcare providers, and pharmaceutical companies are realizing the potential of creating better comparisons of effective treatment outcomes by analyzing long-term data that represent individual patient-based experiences.

(more…)