Therapeutic Environment and Premature newborns Development [PDF]
, 2019 Introduction: Prematurity is the leading cause of neonatal mortality, however, the survival of preterm infants is guaranteed. Prolonged exposure to numerous sensory stimuli during early neonatal intensive care units contributes to the increased ...
Calado, Gabriela, Costa, Mónica
core +1 more source
Anaesthesia and Intensive Care [PDF]
, 2004 The anaesthetist has seen his role steadily expand and it is hard to think of one medical specialty in which anaesthetists are not involved at least to some extent.
Aquilina, Andrew, Sciberras, Stephen C.
core
Diagnostic errors in paediatric cardiac intensive care [PDF]
, 2018 IntroductionDiagnostic errors cause significant patient harm and increase costs. Data characterising such errors in the paediatric cardiac intensive care population are limited.
Aiyagari, Ranjit +7 more
core +2 more sources
ricu: R's Interface to Intensive Care Data [PDF]
arXiv, 2021 Providing computational infrastructure for handling diverse intensive care unit (ICU) datasets, the R package 'ricu' enables writing dataset-agnostic analysis code, thereby facilitating multi-center training and validation of machine learning models. The package is designed with an emphasis on extensibility both to new datasets as well as clinical data
arxiv
An Electronic Delphi Study to Establish Pediatric Intensive Care Nursing Research Priorities in Twenty European Countries* [PDF]
, 2014 OBJECTIVES:: To identify and to establish research priorities for pediatric intensive care nursing science across Europe. DESIGN:: A modified three-round electronic Delphi technique was applied.
Latour, Jos M. +3 more
core +3 more sources
Optimal discharge of patients from intensive care via a data-driven policy learning framework [PDF]
arXiv, 2021 Clinical decision support tools rooted in machine learning and optimization can provide significant value to healthcare providers, including through better management of intensive care units. In particular, it is important that the patient discharge task addresses the nuanced trade-off between decreasing a patient's length of stay (and associated ...
arxiv
Classifying the evolution of COVID-19 severity on patients with combined dynamic Bayesian networks and neural networks [PDF]
arXiv, 2023 When we face patients arriving to a hospital suffering from the effects of some illness, one of the main problems we can encounter is evaluating whether or not said patients are going to require intensive care in the near future. This intensive care requires allotting valuable and scarce resources, and knowing beforehand the severity of a patients ...
arxiv
Long-term cognitive outcomes among unselected ventilated and non-ventilated ICU patients
Journal of Intensive Care, 2017 Background Cognitive dysfunction is an important long-term complication of critical illness associated with reduced quality of life, increase in healthcare costs, and institutionalization.
José Raimundo A. de Azevedo +8 more
doaj +1 more source
Optimizing Medical Treatment for Sepsis in Intensive Care: from Reinforcement Learning to Pre-Trial Evaluation [PDF]
arXiv, 2020 Our aim is to establish a framework where reinforcement learning (RL) of optimizing interventions retrospectively allows us a regulatory compliant pathway to prospective clinical testing of the learned policies in a clinical deployment. We focus on infections in intensive care units which are one of the major causes of death and difficult to treat ...
arxiv
Interdisciplinary communication in the intensive care unit [PDF]
, 2007 Background. Patient safety research has shown poor communication among intensive care unit (ICU) nurses and doctors to be a common causal factor underlying critical incidents in intensive care.
B.H. Cuthbertson +26 more
core +1 more source