Predicting ARDS using the MIMIC II physiological database - Archive ouverte HAL Access content directly
Conference Papers Year :

Predicting ARDS using the MIMIC II physiological database

(1) , (2) , (1) , (1)
1
2
Hassan Amoud
  • Function : Author
  • PersonId : 863613
Ziad Fawal
  • Function : Author

Abstract

Acute Respiratory Distress Syndrome (ARDS) is a critical lung condition occurring in ill patients. Like many other cardiac disorders, ARDS can be assessed by physiological measurements. This study aims to predict ARDS in hospitalized patients using only physiological signals as heart rate and breathing rate. An approach based on hypothesis testing is developed to detect whether subjects' signals deviate from their initial states. The approach is applied on mechanically ventilated subjects in the MIMIC II database. As results, a sensitivity going up to 85% is achieved, with a prediction remaining possible before 24 hours of ARDS occurrence.
Not file

Dates and versions

hal-02358782 , version 1 (12-11-2019)

Identifiers

Cite

Aline Taoum, Farah Mourad-Chehade, Hassan Amoud, Ziad Fawal. Predicting ARDS using the MIMIC II physiological database. 2016 IEEE International Multidisciplinary Conference on Engineering Technology (IMCET), Nov 2016, Beirut, Lebanon. pp.47-51, ⟨10.1109/IMCET.2016.7777425⟩. ⟨hal-02358782⟩
14 View
0 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More