Author + information
- Received April 14, 1995
- Revision received March 15, 1996
- Accepted April 2, 1996
- Published online August 1, 1996.
- Dipti Itchhaporia, MDa,*,
- Peter B. Snow, PhD*,
- Robert J. Almassy, MS† and
- William J. Oetgen, MD, MBA, FACCa
- ↵*Address for correspondence: Dr. Dipti Itchhaporia, Division of Cardiology, Stanford Medical Center, 300 Pasteur Drive, H2321, Stanford, California 94305.
Artificial neural networks are a form of artificial computer intelligence that have been the subject of renewed research interest in the last 10 years. Although they have been used extensively for problems in engineering, they have only recently been applied to medical problems, particularly in the fields of radiology, urology, laboratory medicine and cardiology. An artificial neural network is a distributed network of computing elements that is modeled after a biologic neural system and may be implemented as a computer software program. It is capable of identifying relations in input data that are not easily apparent with current common analytic techniques. The functioning artificial neural network's knowledge is built on learning and experience from previous input data. On the basis of this prior knowledge, the artificial neural network can predict relations found in newly presented data sets. In cardiology, artificial neural networks have been successfully applied to problems in the diagnosis and treatment of coronary artery disease and myocardial infarction, in electrocardiographic interpretation and detection of arrhythmias and in image analysis in cardiac radiography and sonography. This report focuses on the current status of artificial neural network technology in cardiovascular medical research.
This study was supported in part by Georgetown University, Washington, D. C. and by Kaman Sciences Corporation, Colorado Springs and Alexandria.
- Received April 14, 1995.
- Revision received March 15, 1996.
- Accepted April 2, 1996.
- American College of Cardiology