Speaker: Diana Rocha - CIDMA, University of Aveiro
Title of the talk: Bayesian methodology to obtain individual trajectories of HIV patients
Abstract: The development of personalized HIV treatment plans is based on the evaluation of the status of the patient. In this task, noninvasive individual markers, such as the viral load (VL) values and the counts of 𝐶𝐷4+T cells over time, play a prominent role. This work aims at contributing to the accurate characterization of the temporal evolution of the patient status with the development of a tool built upon a mathematical model, that describes the VL and 𝐶𝐷4+T temporal dynamics, whose parameters are estimated from (sparse) temporal observations of the patient of the clinical markers.The parameters of a mathematical model can be estimated from simulation-based approaches, such as the Markov Chain Monte Carlo (MCMC), despite being computationally demanding. More recently, Approximate Bayesian Computation-based (ABC) approaches became promising alternatives to overcome the MCMC computational drawback. In this work, ABC-based approaches are further explored aiming to improve the estimation process while increasing its computational efficiency.
Diana Rocha, PhD student of Applied Mathematics in the Mathematics Department of the University of Aveiro. She received an M.Sc. degree in Quantitative Methods in Economics and Management and graduated in Mathematics from the University of Porto, Portugal, in 2012 and 2010, respectively. Presently she is Microsoft Dynamics 365 developer in a consultant company and writing her PhD thesis. She is interested in mathematics, informatics, and the education of mathematics. Her research interests include applied statistics, computational statistics, and epidemiological models.
Research gate: https://www.researchgate.net/profile/Diana-Rocha-6.