Since about twenty years, the otoneurology functional exploration possesses auditory tool to analyze objectively the state of the nervous conduction of additive pathway. In this paper, we present a new classification approach based on the Hidden Markov Models (HMM) which used to design a Computer aided medical diagnostic (CAMD) tool that asserts auditory pathologies based on Brain-stem Evoked Response Auditory based biomedical test, which provides an effective measure of the integrity of the auditory pathway. Case study, experimental results and comparison with a conventional neural networks models have been reported and discussed.
CITATION STYLE
Lazli, L., Boukadoum, M., Laskri, M. T., & Aït-Mohamed, O. (2017). Diagnosis of auditory pathologies with hidden markov models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10208 LNCS, pp. 118–133). Springer Verlag. https://doi.org/10.1007/978-3-319-56148-6_10
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