Autoregressive Hidden Markov Models for the Early Detection of Neonatal Sepsis

IEEE Journal of Biomedical and Health Informatics

Volumn 18, Issue 5, 2014, Pages 1560-1570

  Stanculescu, Ioan ^a   Williams, Christopher K I ^a   Freer, Yvonne ^b  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

^b UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

Autoregressive hidden Markov model (AR HMM); intensive care; neonatal sepsis; real time inference

Indexed keywords

BLOOD; INTENSIVE CARE UNITS; NEONATAL MONITORING; TRELLIS CODES;

AUTO-REGRESSIVE; INTENSIVE CARE; LABORATORY TESTING; NEONATAL INTENSIVE CARE UNITS; NEONATAL SEPSIS; REAL-TIME INFERENCE; REAL-TIME PREDICTION; RESEARCH QUESTIONS;

HIDDEN MARKOV MODELS;

OXYGEN;

BLOOD; BRADYCARDIA; HEART RATE; HUMAN; INFANT, NEWBORN, DISEASES; NEWBORN; PHYSIOLOGIC MONITORING; PROBABILITY; PROCEDURES; RECEIVER OPERATING CHARACTERISTIC; SEPSIS; STATISTICAL MODEL;

BRADYCARDIA; HEART RATE; HUMANS; INFANT, NEWBORN; INFANT, NEWBORN, DISEASES; MARKOV CHAINS; MODELS, STATISTICAL; MONITORING, PHYSIOLOGIC; OXYGEN; ROC CURVE; SEPSIS;

EID: 84927170042     PISSN: 21682194     EISSN: 21682208     Source Type: Journal    
DOI: 10.1109/JBHI.2013.2294692     Document Type: Article

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