HeMA: A hierarchically enriched machine learning approach for managing false alarms in real time: A sepsis prediction case study.
Zeyu LiuAnahita KhojandiAkram MohammedXueping LiLokesh ChinthalaRobert L. DavisRishikesan KamaleswaranPublished in: Comput. Biol. Medicine (2021)
Keyphrases
- false alarms
- real time
- machine learning
- case study
- number of false alarms
- prediction accuracy
- detection rate
- false alarm rate
- target detection
- high rate
- false positives
- learning algorithm
- information extraction
- knowledge acquisition
- real world
- text classification
- learning systems
- vision system
- prediction error
- low cost
- computer vision
- model selection
- detection algorithm
- machine learning methods
- statistical methods
- software development
- knowledge management
- explanation based learning
- supervised learning
- artificial intelligence