Markov chains provide a fundamental framework for modelling stochastic processes, where the next state depends solely on the current state. Hidden Markov models (HMMs) extend this framework by ...

Markov chain models and phase-type distributions have emerged as powerful tools in healthcare analytics, offering a robust framework for understanding and predicting patient trajectories throughout ...

What Is Markov Chain Monte Carlo? Markov Chain Monte Carlo (MCMC) is a powerful technique used in statistics and various scientific fields to sample from complex probability distributions. It is ...

Online bipartite matching (OBM) has a rich history in the literature of online algorithms, where it has been an influential problem inspiring many algorithms and techniques. This problem of obtaining ...

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 ...

This is a preview. Log in through your library . Abstract We describe movement patterns of hatchery-raised, juvenile, spring chinook salmon, Oncorhynchus tshawytscha, using a two-state Markov chain ...

Antitumor activity of MP0250, a bispecific VEGF- and HGF-targeting darpin, in patient-derived xenograft models. This is an ASCO Meeting Abstract from the 2014 ASCO Annual Meeting I. This abstract does ...