Seminar August 22TH, 2023

Dra Javiera Leniz M.
MD, MSC, MPH, PhD

Title: Big data and health research: challenges and opportunities in Chile

Abstract: Health data, also known as routine data, has gained an important space in
epidemiologic research in the last years. The volume of cumulative data, along with the
evolution of technology use in health have made this information particularly attractive for
research. In this talk we will discuss the use of big clinical and administrative health databases
in research related to end of life care, in the context of the experience of our invited speaker
with the use of clinical and administrative records in the UK and Chile. The discussion will
consider the strengths, opportunities and limitations of the use of health data in general and how
we can advance in this area in Chile.

Bio: Javiera Léniz is an specialist in family medicine, Master in Epidemiology and Public Health
and PhD in Palliative Care from King’s College London in UK. She was a researcher in the
Cicely Saunders Institute of Palliative Care (King’s College London) where she worked doing
research in people with dementia at the end of life with clinical and administrative records in the
UK. Currently, she is a professor at the Department of Public Health at PUC. Her research line
is centred on the evaluation of quality of life at the end of life, cognitive decline, primary care
and the use of clinical and administrative records in research.

Javier Ernesto Bisbal Zenteno

Title: Advanced AI and physics for enhanced 4D flow MRI post-processing.

Abstract: Four-dimensional Magnetic Resonance Imaging, also known as “4D flow MRI”,
provides a time-resolved velocity field in a volumetric region of interest. In the context of cardiac
imaging, 4D flow MRI offers advanced hemodynamic parameters to characterize cardiovascular
diseases. However, 4D flow MRI suffers from multiple sources of noise, as well as
time-consuming and user-dependent post-processing steps. I In my research, I am focusing on
innovative techniques aimed at denoising 4D flow data and automating the process of plane
reformatting This plane reformatting is a pivotal procedure for the accurate assessment of
vessel hemodynamics. Specifically, my approach involves leveraging physics-informed artificial
intelligence for robust denoising, and employing deep reinforcement learning to achieve
automated plane reformatting.

Bio: Javier is an electric engineer with experience in biomedical research, machine learning and
artificial intelligence. He holds a master’s degree from Pontificia Universidad Católica de Chile
(PUC) and is currently in pursuit of his PhD at PUC, focusing on the fusion of AI and physics for
advanced flow imaging techniques.

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