[go: up one dir, main page]

Herrmann et al., 2021 - Google Patents

Model-based selection of most informative diagnostic tests and test parameters

Herrmann et al., 2021

View HTML
Document ID
17727781200754360371
Author
Herrmann S
Dietz M
Publication year
Publication venue
Acta Acustica

External Links

Snippet

Given the complexity of most brain and body processes, it is often not possible to relate experimental data from an individual to the underlying subject-specific physiology or pathology. Computer simulations of these processes have been suggested to assist in …
Continue reading at acta-acustica.edpsciences.org (HTML) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/345—Medical expert systems, neural networks or other automated diagnosis
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R25/00—Deaf-aid sets providing an auditory perception; Electric tinnitus maskers providing an auditory perception
    • H04R25/70—Adaptation of deaf aid to hearing loss, e.g. initial electronic fitting
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/12—Audiometering Evaluation or the auditory system, not limited to hearing capacity
    • A61B5/121—Audiometering Evaluation or the auditory system, not limited to hearing capacity evaluating hearing capacity

Similar Documents

Publication Publication Date Title
Baby et al. A convolutional neural-network model of human cochlear mechanics and filter tuning for real-time applications
Pardo-Vazquez et al. The mechanistic foundation of Weber’s law
Billings et al. Predicting perception in noise using cortical auditory evoked potentials
Rabinowitz et al. Contrast gain control in auditory cortex
EP2238899B1 (en) Efficient evaluation of hearing ability
Kollmeier et al. Sentence recognition prediction for hearing-impaired listeners in stationary and fluctuation noise with FADE: Empowering the attenuation and distortion concept by Plomp with a quantitative processing model
Houtgast et al. On the auditory and cognitive functions that may explain an individual's elevation of the speech reception threshold in noise
Jennings et al. Evaluating the effects of olivocochlear feedback on psychophysical measures of frequency selectivity
Drakopoulos et al. A convolutional neural-network framework for modelling auditory sensory cells and synapses
Smalt et al. Modeling the time-varying and level-dependent effects of the medial olivocochlear reflex in auditory nerve responses
Buran et al. Predicting synapse counts in living humans by combining computational models with auditory physiology
CN115362689B (en) Method based on artificial neural network and use thereof, hearing device and computer program product
Hossain et al. Reference-free assessment of speech intelligibility using bispectrum of an auditory neurogram
Keshishzadeh et al. Towards personalized auditory models: Predicting individual sensorineural hearing-loss profiles from recorded human auditory physiology
DE102015218948A1 (en) Apparatus and method for determining a medical health parameter of a subject by means of voice analysis
Panda et al. Hearing dummies: Individualized computer models of hearing impairment
Völker et al. Hearing aid fitting and fine-tuning based on estimated individual traits
McMillan et al. A Bayesian perspective on tinnitus pitch matching
Herrmann et al. Model-based selection of most informative diagnostic tests and test parameters
Wirtzfeld et al. Predicting the quality of enhanced wideband speech with a cochlear model
Chesnaye et al. A group sequential test for ABR detection
Ellis et al. Using machine learning and the national health and nutrition examination survey to classify individuals with hearing loss
Lopez et al. A clinical test battery for Better hEAring Rehabilitation (BEAR): Towards the prediction of individual auditory deficits and hearing-aid benefit
Petersen Hearing-aid directionality improves neural speech tracking in older hearing-impaired listeners
Trevino et al. Development of a multi-category psychometric function to model categorical loudness measurements