TY - GEN
T1 - Automatic diagnosis of hypoacusia with associative memories
AU - Acevedo, Elena
AU - Calderón, Julia
AU - Acevedo, Antonio
AU - Felipe, Federico
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/11/12
Y1 - 2018/11/12
N2 - Hypoacusia 1 is the reduction in hearing ability. An early diagnose could avoid the complete loss of the sense of hearing. We propose a modification of modified Johnson-Möbius together with a tool of Artificial Intelligence to diagnose hearing losing. The modified Johnson-Möbius has been showed suitable results when it was used with Alpha-Beta associative memories that deal with binary numbers. Now, we modified this code to apply it to Morphological associative memories whose set of numbers is real-type. Based on the improved results of Alpha-Beta memories with this codification, we applied the modification of the code to improve the performance of Morphological memories with feature selection. The results are suitable to implement an automatic system for hypoacusia diagnosis.
AB - Hypoacusia 1 is the reduction in hearing ability. An early diagnose could avoid the complete loss of the sense of hearing. We propose a modification of modified Johnson-Möbius together with a tool of Artificial Intelligence to diagnose hearing losing. The modified Johnson-Möbius has been showed suitable results when it was used with Alpha-Beta associative memories that deal with binary numbers. Now, we modified this code to apply it to Morphological associative memories whose set of numbers is real-type. Based on the improved results of Alpha-Beta memories with this codification, we applied the modification of the code to improve the performance of Morphological memories with feature selection. The results are suitable to implement an automatic system for hypoacusia diagnosis.
KW - Artificial Intelligence
KW - Associative Memories
KW - Codification
KW - Diagnosis
KW - Hypoacusia
UR - http://www.scopus.com/inward/record.url?scp=85064487089&partnerID=8YFLogxK
U2 - 10.1145/3293614.3293654
DO - 10.1145/3293614.3293654
M3 - Contribución a la conferencia
AN - SCOPUS:85064487089
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the Euro American Conference on Telematics and Information Systems, EATIS 2018
PB - Association for Computing Machinery
T2 - 2018 Euro American Conference on Telematics and Information Systems, EATIS 2018
Y2 - 12 November 2018 through 15 November 2018
ER -