Discrete-time hidden Markov models are a broadly useful class of latent variable models with applications in areas such as speech recognition, bioinformatics, and climate data analysis. It is common ...

Background Conventionally, frequentist approach has been used to model health state valuation data. Recently, researchers started to explore the use of Bayesian methods in this area. Objectives This ...

Markov Models for disease progression are common in medical decision making (see references below). The parameters in a Markov model can be estimated by observing the time it takes patients in any ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I closely examine an innovative way of ...