NDLI: Adapting ECG morphology changes from reduced-lead set by specifically trained algorithms for acute ischemia detection

Content Provider	IEEE Xplore Digital Library
Author	Xue, J.Q.
Copyright Year	2007
Description	Author affiliation: GE Healthcare, Wauwatosa, WI (Xue, J.Q.)
Abstract	The reduced lead set in this study consists of a subset of 12-lead set with all the same limb leads, plus v1 and v5 chest leads. They were then converted to 12-lead signals with a trained matrix. The aims of this study are to evaluate the changes of morphology due to the conversion and the possibility of adapting the changes with the new criteria trained with a large ischemia ECG database. For the evaluation, we first applied the standard 12 lead computerized algorithm to the converted 12-lead ECGs. We then applied 2 training algorithms to the converted 12-lead ECG to obtain the specific criteria. One algorithm is based on neural network models, and the other is based on the binary-tree classification model with automatically induced rules (C4.5). The study used the chest pain databases from Mayo Clinic and Medical College of Wisconsin, which include ECGs from 993 anterior MI patients, 1187 inferior MI patients and 1987 Nonischemic patients based on their final confirmation with Cathlab or Biomarker tests. The results show that, without retraining, the reduced-lead set achieved 53% sensitivity for Inferior MI, compared with 54% from standard 12-lead set, and with both specificity of 99%. For anterior MI, the sensitivity of reduced lead set is 37%, compared to the 46% for standard 12 lead. After retraining, the reduced lead set has a sensitivity of anterior MI 56%, compared to a retrained standard 12 lead set of 57%, with specificity above 98% for both lead sets.
Starting Page	709
Ending Page	712
File Size	1582179
Page Count	4
File Format	PDF
ISBN	9781424425334
ISSN	02766547
DOI	10.1109/CIC.2007.4745584
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Computers in Cardiology(CinC)
Subject Keyword	Electrocardiography Morphology Ischemic pain Neural networks Databases Decision trees Medical services Physics computing Matrix converters Educational institutions
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Adapting ecg morphology changes from reduced-lead set by specifically trained algorithms for acute ischemia detection.

Using a Cell-to-ECG model to evaluate ischemia detection from different lead sets

Simulating ECG changes during acute myocardial ischemia

Using a cell-to-ecg model to evaluate ischemia detection from different lead sets.

A Novel Neural-Network Model for Deriving Standard 12-Lead ECGs From Serial Three-Lead ECGs: Application to Self-Care

Electrocardiographic Systems With Reduced Numbers of Leads—Synthesis of the 12-Lead ECG

Detection of acute myocardial ischemia by vessel-specific leads derived from reduced lead sets

Use of neural networks in detection of ischemic episodes from ECG leads

One-lead ischemia detection using a new backpropagation algorithm and the European ST-T database

Adapting ECG morphology changes from reduced-lead set by specifically trained algorithms for acute ischemia detection

Similar Documents

Adapting ecg morphology changes from reduced-lead set by specifically trained algorithms for acute ischemia detection.

Using a Cell-to-ECG model to evaluate ischemia detection from different lead sets

Simulating ECG changes during acute myocardial ischemia

Using a cell-to-ecg model to evaluate ischemia detection from different lead sets.

A Novel Neural-Network Model for Deriving Standard 12-Lead ECGs From Serial Three-Lead ECGs: Application to Self-Care

Electrocardiographic Systems With Reduced Numbers of Leads—Synthesis of the 12-Lead ECG

Detection of acute myocardial ischemia by vessel-specific leads derived from reduced lead sets

Use of neural networks in detection of ischemic episodes from ECG leads

One-lead ischemia detection using a new backpropagation algorithm and the European ST-T database

Adapting ECG morphology changes from reduced-lead set by specifically trained algorithms for acute ischemia detection