AIMC Topic: Hearing Loss, Sensorineural
Clear Filters Showing 11 to 20 of 31 articles
Artificial Neural Network-Assisted Classification of Hearing Prognosis of Sudden Sensorineural Hearing Loss With Vertigo.
IEEE journal of translational engineering in health and medicine
Feb 6, 2023
This study aimed to determine the impact on hearing prognosis of the coherent frequency with high magnitude-squared wavelet coherence (MSWC) in video head impulse test (vHIT) among patients with sudden sensorineural hearing loss with vertigo (SSNHLV)...
In silico investigation on structure-function relationship of members belonging to the human SLC52 transporter family.
Proteins
Dec 23, 2022
Riboflavin is an essential water-soluble vitamin that needs to be provided through the diet because of the conversion into flavin adenine dinucleotide (FAD) and flavin mononucleotide (FMN), important cofactors in hundreds of flavoenzymes. The adsorpt...
Robotic cochlear implantation in post-meningitis ossified cochlea.
American journal of otolaryngology
Oct 22, 2022
AIM: To report the experience of an image-guided and navigation-based robot arm as an assistive surgical tool for cochlear implantation in a case with a labyrinthitis ossificans.
PhenoApt leverages clinical expertise to prioritize candidate genes via machine learning.
American journal of human genetics
Jan 20, 2022
In recent years, exome sequencing (ES) has shown great utility in the diagnoses of Mendelian disorders. However, after rigorous filtering, a typical ES analysis still involves the interpretation of hundreds of variants, which greatly hinders the rapi...
A deep learning approach to quantify auditory hair cells.
Hearing research
Jul 22, 2021
Hearing loss affects millions of people worldwide. Yet, there are still no curative therapies for sensorineural hearing loss. Frequent causes of sensorineural hearing loss are due to damage or loss of the sensory hair cells, the spiral ganglion neuro...
Predicting hearing recovery following treatment of idiopathic sudden sensorineural hearing loss with machine learning models.
American journal of otolaryngology
Jan 4, 2021
PURPOSE: Idiopathic sudden sensorineural hearing loss (ISSHL) is an emergency otological disease, and its definite prognostic factors remain unclear. This study applied machine learning methods to develop a new ISSHL prognosis prediction model.
Transient-evoked otoacoustic emission signals predicting outcomes of acute sensorineural hearing loss in patients with Ménière's disease.
Acta oto-laryngologica
Jan 31, 2020
Fluctuating hearing loss is characteristic of Ménière's disease (MD) during acute episodes. However, no reliable audiometric hallmarks are available for counselling the hearing recovery possibility. To find parameters for predicting MD hearing outco...
Using Machine Learning to Predict Sensorineural Hearing Loss Based on Perilymph Micro RNA Expression Profile.
Scientific reports
Mar 4, 2019
Hearing loss (HL) is the most common neurodegenerative disease worldwide. Despite its prevalence, clinical testing does not yield a cell or molecular based identification of the underlying etiology of hearing loss making development of pharmacologica...
Predicting the hearing outcome in sudden sensorineural hearing loss via machine learning models.
Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery
Feb 20, 2018
OBJECTIVE: Sudden sensorineural hearing loss (SSHL) is a multifactorial disorder with high heterogeneity, thus the outcomes vary widely. This study aimed to develop predictive models based on four machine learning methods for SSHL, identifying the be...
A semi-supervised Support Vector Machine model for predicting the language outcomes following cochlear implantation based on pre-implant brain fMRI imaging.
Brain and behavior
Oct 12, 2015
INTRODUCTION: We developed a machine learning model to predict whether or not a cochlear implant (CI) candidate will develop effective language skills within 2 years after the CI surgery by using the pre-implant brain fMRI data from the candidate.
Child, Preschool
Hearing Loss, Sensorineural
Language
ROC Curve
Language Tests
Area Under Curve
Humans
Treatment Outcome
Female
Support Vector Machine
Image Interpretation, Computer-Assisted
Brain
Male
Magnetic Resonance Imaging
Cochlear Implantation
Prognosis
Infant
Models, Neurological
Hypnotics and Sedatives
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823