Classifying human audiometric phenotypes of age-related hearing loss from animal models

JARO - Journal of the Association for Research in Otolaryngology

Volumn 14, Issue 5, 2013, Pages 687-701

  Dubno, Judy R ^a   Eckert, Mark A ^a   Lee, Fu Shing ^a   Matthews, Lois J ^a   Schmiedt, Richard A ^a  

^a MEDICAL UNIVERSITY OF SOUTH CAROLINA   (United States)

Author keywords

animal models; audiogram classification; endocochlear potential; metabolic presbyacusis; sensory presbyacusis; supervised machine learning classifiers

Indexed keywords

ADULT; AGE DISTRIBUTION; AGED; ARTICLE; AUDIOMETRY; CLASSIFIER; COCHLEA; DISEASE CLASSIFICATION; FEMALE; HEARING IMPAIRMENT; HUMAN; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; NOISE; NONHUMAN; PHENOTYPE; PRESBYACUSIS; PRIORITY JOURNAL;

AGED; AGED, 80 AND OVER; ANIMALS; ARTIFICIAL INTELLIGENCE; AUDIOMETRY, PURE-TONE; AUDITORY THRESHOLD; DATABASES, FACTUAL; DISEASE MODELS, ANIMAL; FEMALE; HEARING LOSS, NOISE-INDUCED; HUMANS; MALE; MIDDLE AGED; PHENOTYPE; PRESBYCUSIS; REPRODUCIBILITY OF RESULTS;

EID: 84884287238     PISSN: 15253961     EISSN: 14387573     Source Type: Journal    
DOI: 10.1007/s10162-013-0396-x     Document Type: Article

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