Objectives The objective of this article is to describe the unique challenges and present
potential solutions and approaches for economic evaluations of precision medicine (PM) …

Background Micro-simulation models of risk-factors and chronic diseases are built
increasingly often, and each model starts with an initial population. Constructing such …

Treatment decisions in healthcare often carry lifelong consequences that can be challenging
to foresee. As such, tools that visualize and estimate outcome after different lifetime …

Background Models that forecast non-communicable disease rates are poorly designed to
predict future changes in trend because they are based on exogenous measures of disease …

One method for rapid learning is to use data from electronic medical records (EMRs) to help
build and validate large-scale, physiology-based simulation models. These models can than …

Colorectal cancer (CRC) is deadly if not found early. Any protocols developed for screening
and surveillance and any policy decisions regarding the availability of CRC resources …

Objectives: Calibrating a disease simulation model's outputs to existing clinical data is vital
to generate confidence in the model's predictive ability. Calibration involves two challenges …

Background Machine learning (ML) methods have shown great potential in predicting
colorectal cancer (CRC) survival. However, the ML models introduced thus far have mainly …