Utilizing Theory of Machine Learning and Signal Processing to Incorporate Physiological Signals, Assessment of Sympathovagal Imbalance, Conventional and Novel Inflammation and Immune Biomarkers to Develop and Validate the Clinical Prediction Models

Chen, Kuan-Fu (PI)
Chan, Yi Ling (CoPI)
Chen, Chun-Hsien (CoPI)
Han, Shih Tsung (CoPI)
Lin, Chen (CoPI)
Lo, Men Tzung (CoPI)
Tseng, Yi-Ju (CoPI)
Yu, Jau-Song (CoPI)

Project: National Science and Technology Council › National Science and Technology Council Academic Grants

Project IDs

Project ID:PC10801-0191
External Project ID:MOST107-2314-B182-052-MY2

Status	Finished
Effective start/end date	01/08/19 → 31/07/20

Keywords

sepsis
biomarker
clinical prediction rule
emergency medicine
latent class analysis
cohort study
procalcitonin
c-reactive protein
causal relationship
recursive partitioning algorithm
risk factor
heart rate variability
non-invasive monitoring
signal processing
machine learning
artificial intelligence
support vector machine
artificial neural network

Access Project

https://www.grb.gov.tw/search/planDetail?id=12811941