Modelling Infective Exacerbations in Cystic Fibrosis
Lead Research Organisation:
University of Cambridge
Department Name: Medicine
Abstract
The aim of this project is to use the large dataset of daily physiological telemetry recordings and longitudinal clinical metadata collected through the UK SmartcareCF study to develop generative graphical models of the processes leading to APEs to i) gain insight into the pathophysiology of APEs, which might subsequently be testable clinically or experimentally, and ii) develop algorithms that might predict the onset of APEs, which could potentially be used clinically to trigger early antibiotic therapy.
People |
ORCID iD |
Rodrigo Floto (Primary Supervisor) | |
Damian Sutcliffe (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/R511870/1 | 30/09/2017 | 29/09/2023 | |||
2109901 | Studentship | EP/R511870/1 | 30/09/2018 | 29/09/2022 | Damian Sutcliffe |