Prediction of clinicians' treatment in preterm infants with suspected late-onset sepsis - An ML approach

Proceedings of the 13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018

Volumn , Issue , 2018, Pages 1177-1182

  Hu, Yifei ^a   Lee, Vincent C S ^a   Tan, Kenneth ^b  

^a MONASH UNIVERSITY   (Australia)

^b MONASH CHILDREN S HOSPITAL   (Australia)

Author keywords

machine learning; neonatal sepsis; prediction; vital signs (key words)

Indexed keywords

ARTIFICIAL INTELLIGENCE; FORECASTING; INDUSTRIAL ELECTRONICS; NONINVASIVE MEDICAL PROCEDURES;

CLINICAL DECISION; KEY WORDS; NEONATAL SEPSIS; NONINVASIVE METHODS; ON-MACHINES; PREDICTIVE MODELS; PRETERM INFANTS; VITAL SIGN;

LEARNING SYSTEMS;

EID: 85050146504     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIEA.2018.8397888     Document Type: Conference Paper

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