Artificial Intelligence Applications in Otology: A State of the Art Review

Objective auditory brainstem response classification using machine learning

(2019) Richard M. McKearney et al.   INTERNATIONAL JOURNAL OF AUDIOLOGY

Artificial Intelligence for the Otolaryngologist: A State of the Art Review

(2019) Andrés M. Bur et al.   OTOLARYNGOLOGY-HEAD AND NECK SURGERY

A contemporary review of machine learning in otolaryngology-head and neck surgery

(2019) Matthew G. Crowson et al.   LARYNGOSCOPE

Artificial intelligence in medicine: current trends and future possibilities

(2018) Varun H Buch et al.   BRITISH JOURNAL OF GENERAL PRACTICE

Predicting the hearing outcome in sudden sensorineural hearing loss via machine learning models

(2018) D. Bing et al.   CLINICAL OTOLARYNGOLOGY

Cochlea CT radiomics predicts chemoradiotherapy induced sensorineural hearing loss in head and neck cancer patients: A machine learning and multi-variable modelling study

(2018) Hamid Abdollahi et al.   Physica Medica-European Journal of Medical Physics

Machine Learning Models for the Hearing Impairment Prediction in Workers Exposed to Complex Industrial Noise

(2018) Yanxia Zhao et al.   EAR AND HEARING

The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care

(2018) Matthieu Komorowski et al.   NATURE MEDICINE

Dermatologist-level classification of skin cancer with deep neural networks

(2017) Andre Esteva et al.   NATURE

ELHnet: a convolutional neural network for classifying cochlear endolymphatic hydrops imaged with optical coherence tomography

(2017) George S. Liu et al.   Biomedical Optics Express

Mining balance disorders' data for the development of diagnostic decision support systems

(2016) T.P. Exarchos et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

(2016) Varun Gulshan et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Smartphone-Based System for Learning and Inferring Hearing Aid Settings

(2016) Gabriel Aldaz et al.   Journal of the American Academy of Audiology

EMBalance - validation of a decision support system in the early diagnostic evaluation and management plan formulation of balance disorders in primary care: study protocol of a feasibility randomised controlled trial

(2016) Laura Rammazzo et al.   Trials

Otitis Media Diagnosis for Developing Countries Using Tympanic Membrane Image-Analysis

(2016) Hermanus C. Myburgh et al.   EBioMedicine

Deep learning

(2015) Yann LeCun et al.   NATURE

A Regression Approach to Speech Enhancement Based on Deep Neural Networks

(2015) Yong Xu et al.   IEEE-ACM Transactions on Audio Speech and Language Processing

Machine learning-based assessment tool for imbalance and vestibular dysfunction with virtual reality rehabilitation system

(2014) Shih-Ching Yeh et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach

(2014) Mohsen Aliabadi et al.   INTERNATIONAL ARCHIVES OF OCCUPATIONAL AND ENVIRONMENTAL HEALTH

Real-Life Efficacy and Reliability of Training a Hearing Aid

(2013) Gitte Keidser et al.   EAR AND HEARING

Why do people fitted with hearing aids not wear them?

(2013) Abby McCormack et al.   INTERNATIONAL JOURNAL OF AUDIOLOGY

Integrating cognitive and peripheral factors in predicting hearing-aid processing effectiveness

(2013) James M. Kates et al.   JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA

Using Trainable Hearing Aids to Examine Real-World Preferred Gain

(2009) H Gustav Mueller et al.   Journal of the American Academy of Audiology

Neural network classification of otoneurological data and its visualization

(2008) Markku Siermala et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Classification of Otoneurological Cases According to Bayesian Probabilistic Models

(2008) Katja Miettinen et al.   JOURNAL OF MEDICAL SYSTEMS