Marine Flechet

Marine Flechet
Philips | Philips · Collaborative Care Solutions

PhD

About

15
Publications
1,150
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249
Citations
Introduction
Marine Flechet is an Artificial Intelligence Scientist at Philips Research. Her role in the department of Collaborative Care Solutions involves developing patient stratification-based solutions. Previously, Marine conducted a PhD at the Laboratory of Intensive Care Medicine, University of Leuven. Marine conducted research in Data Mining and Engineering applied to Intensive Care. Her PhD thesis was entitle "Clinical prediction models in critical illness: from computer to bedside".
Additional affiliations
December 2018 - present
KU Leuven
Position
  • PostDoc Position
Description
  • Laboratory of Intensive Care Medicine
October 2014 - November 2018
KU Leuven
Position
  • PhD Student

Publications

Publications (15)
Article
Purpose Early diagnosis of acute kidney injury (AKI) remains a major challenge. We developed and validated AKI prediction models in adult ICU patients and made these models available via an online prognostic calculator. We compared predictive performance against serum neutrophil gelatinase-associated lipocalin (NGAL) levels at ICU admission. Metho...
Article
Full-text available
Background: Early diagnosis of acute kidney injury (AKI) is a major challenge in the intensive care unit (ICU). The AKIpredictor is a set of machine-learning-based prediction models for AKI using routinely collected patient information, and accessible online. In order to evaluate its clinical value, the AKIpredictor was compared to physicians' pre...
Chapter
Objective: The aim of this study is to assess visually the impact of duration and intensity of cerebrovascular autoregulation insults on 6-month neurological outcome in severe traumatic brain injury. Material and methods: Retrospective analysis of prospectively collected minute-by-minute intracranial pressure (ICP) and mean arterial blood pressu...
Article
Objectives: To assess whether near-infrared cerebral tissue oxygen saturation, measured with the FORESIGHT cerebral oximeter (CAS Medical Systems, Branford, CT) predicts PICU length of stay, duration of invasive mechanical ventilation, and mortality in critically ill children after pediatric cardiac surgery. Design: Single-center prospective, ob...
Article
Purpose of review: Big data is the new hype in business and healthcare. Data storage and processing has become cheap, fast, and easy. Business analysts and scientists are trying to design methods to mine these data for hidden knowledge. Neurocritical care is a field that typically produces large amounts of patient-related data, and these data are...
Article
Background In patients with aneurysmal subarachnoid hemorrhage (aSAH) the burden of intracranial pressure (ICP) and its contribution to outcomes remains unclear. In this multicenter study, the independent association between intensity and duration, or “dose,” of episodes of intracranial hypertension and 12-month neurological outcomes was investigat...
Article
Full-text available
Objectives: During the early postoperative period, children with congenital heart disease can suffer from inadequate cerebral perfusion, with possible long-term neurocognitive consequences. Cerebral tissue oxygen saturation can be monitored noninvasively with near-infrared spectroscopy. In this prospective study, we hypothesized that reduced cereb...
Article
Full-text available
Objective: To report on the currently available prediction models for the development of acute kidney injury in heterogeneous adult intensive care units. Methods: A systematic review of clinical prediction models for acute kidney injury in adult intensive care unit populations was carried out. PubMed® was searched for publications reporting on the...
Preprint
Full-text available
Background Augmented renal clearance (ARC) might lead to subtherapeutic plasma levels of drugs with predominant renal clearance. Early identification of ARC remains challenging for the intensive care unit (ICU) physician. We developed and validated the ARC predictor, a clinical prediction model for ARC on the next day during ICU stay, and made it a...
Preprint
Full-text available
Background Augmented renal clearance (ARC) might lead to subtherapeutic plasma levels of drugs with predominant renal clearance. Early identification of ARC remains challenging for the intensive care unit (ICU) physician. We developed and validated the ARC predictor, a clinical prediction model for ARC on the next day during ICU stay, and made it a...
Article
Full-text available
Objectives: Cerebral oximetry by near-infrared spectroscopy is used frequently in critically ill children but guidelines on its use for decision making in the PICU are lacking. We investigated cerebral near-infra-red spectroscopy oximetry in its ability to predict severe acute kidney injury after pediatric cardiac surgery and assessed its additiona...
Article
Objectives: The use of mortality prediction scores in clinical trials in the PICU is essential for comparing patient groups. Because of the decline in PICU mortality over the last decades, leading to a shift toward later deaths, recent trials use 90-day mortality as primary outcome for estimating mortality and survival more accurately. This study...
Article
Background: Elevated blood glucose (BG) concentrations (Hyperglycaemia) are a common complication in critically ill patients. Insulin therapy is commonly used to treat hyperglycaemia, but metabolic variability often results in poor BG control and low BG (hypoglycaemia). Objective: This paper presents a model-based virtual trial method for glycae...
Article
Full-text available
Acute Kidney Injury (AKI) is associated with increased morbidity and mortality in critically ill patients [1]. Early detection and treatment may improve outcome. Previously, we developed a logistic regression (LR) model for early detection of AKI based on routinely collected data available at baseline, ICU admission and at the end of the first day...

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