ANN Based Classification for Heart Defibrillators
Abstract
Current Intra-Cardia defibrillators make use of simple classification algo(cid:173) rithms to determine patient conditions and subsequently to enable proper therapy. The simplicity is primarily due to the constraints on power dissipa(cid:173) tion and area available for implementation. Sub-threshold implementation of artificial neural networks offer potential classifiers with higher perfor(cid:173) mance than commercially available defibrillators. In this paper we explore several classifier architectures and discuss micro-electronic implementation issues.
Cite
Text
Jabri et al. "ANN Based Classification for Heart Defibrillators." Neural Information Processing Systems, 1991.Markdown
[Jabri et al. "ANN Based Classification for Heart Defibrillators." Neural Information Processing Systems, 1991.](https://mlanthology.org/neurips/1991/jabri1991neurips-ann/)BibTeX
@inproceedings{jabri1991neurips-ann,
title = {{ANN Based Classification for Heart Defibrillators}},
author = {Jabri, M. and Pickard, S. and Leong, P. and Chi, Z. and Flower, B. and Xie, Y.},
booktitle = {Neural Information Processing Systems},
year = {1991},
pages = {637-644},
url = {https://mlanthology.org/neurips/1991/jabri1991neurips-ann/}
}