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/}
}