Title :
Exposure of cardiovascular disease diagnostic signs by neural network
Abstract :
A system based on the method of potential functions for pattern recognition was developed. Input vectors length of the designed system is equal to 9 according to the number of electrocardiogram parameters. The number of recognized signs of disease is equal to 6 (hypertrophy of auricle, rhythm and conduction disturbance). The system appeared to be an effective one for usage at polyclinics
Keywords :
cardiovascular system; diseases; electrocardiography; medical signal processing; neural nets; pattern recognition; vectors; ECG analysis; atrium hypertrophy; cardiovascular disease diagnostic signs exposure; conduction disturbance; electrocardiogram parameters; input vectors length; polyclinics; potential functions method; recognized disease signs; rhythm disturbance; Atherosclerosis; Cardiac disease; Cardiovascular diseases; Cities and towns; Design automation; Industrial accidents; Injuries; Medical diagnostic imaging; Neural networks; Registers;
Conference_Titel :
Modern Techniques and Technology, 2001. MTT 2001. Proceedings of the 7th International Scientific and Practical Conference of Students, Post-graduates and Young Scientists
Conference_Location :
Tomsk
Print_ISBN :
0-7803-6346-9
DOI :
10.1109/MTT.2001.983776
