Decision Tree Predictive Learner-Based Approach for False Alarm Detection in ICU.
In this work, a novel method has been proposed for false alarm detection in Intensive Care Unit (ICU) during arrhythmia. To detect false alarm, various inputs are used such as electrocardiogram (ECG) signals, atrial blood pressure (ABP), photoplethysmogram signals (PLETH) and respiration (RESP). The...
| Publicado en: | Journal of Medical Systems Vol. 43; no. 7; pp. 1 - 14 |
|---|---|
| Autores principales: | , , |
| Formato: | algorithm equations & formulas pictorial research tables/charts tracings Journal Article |
| Publicado: |
Springer Nature
Jul2019
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=137182942&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 137182942 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Jul2019 vid: 43 iid: 7 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 137182942 137182942 137182942 10.1007/s10916-019-1337-y 137182942 ppf: 1 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Decision Tree Predictive Learner-Based Approach for False Alarm Detection in ICU. aug: au: Manna, Tishya Swetapadma, Aleena Abdar, Moloud affil: School of Computer Engineering, KIIT University, Bhubaneswar, India sug: subj: Decision Trees Equipment Alarm Systems Intensive Care Units Arrhythmia Machine Learning Methods Computer Input Devices Signal Processing, Computer Assisted Electrocardiography Cardiography, Impedance Human ab: In this work, a novel method has been proposed for false alarm detection in Intensive Care Unit (ICU) during arrhythmia. To detect false alarm, various inputs are used such as electrocardiogram (ECG) signals, atrial blood pressure (ABP), photoplethysmogram signals (PLETH) and respiration (RESP). The inputs are given to decision tree predictive learner (DTPL) based classifier for thedetection of false alarm. The proposed method has an accuracy of 97% for prediction of false alarm in ICU. Theresult of the proposed method is promising which suggest that it can be used effectively for false alarm detection in ICUs. To the best of our knowledge, there is no such assumption based classification approach. pubtype: Academic Journal doctype: algorithm equations & formulas pictorial research tables/charts tracings Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|