Application of machine learning to predict hearing outcomes of tympanoplasty
H Koyama, A Kashio, T Uranaka… - The …, 2023 - Wiley Online Library
Objective This retrospective study aimed to evaluate the performance of machine learning
techniques in predicting air‐bone gap after tympanoplasty compared with conventional …
techniques in predicting air‐bone gap after tympanoplasty compared with conventional …
[HTML][HTML] Machine learning technique reveals prognostic factors of vibrant soundbridge for conductive or mixed hearing loss patients
H Koyama, A Mori, D Nagatomi, T Fujita… - Otology & …, 2021 - journals.lww.com
Objectives: Vibrant Soundbridge (VSB) was developed for treatment of hearing loss, but
clinical outcomes vary and prognostic factors predicting the success of the treatment remain …
clinical outcomes vary and prognostic factors predicting the success of the treatment remain …
Can MRI biomarkers for hearing loss in enlarged vestibular aqueduct be measured reproducibly?
HS Saeed, A Rajai, R Dixon, T Kapadia… - The British journal of …, 2023 - academic.oup.com
Objective: Morphological features of an enlarged endolymphatic duct (ED) and sac (ES) are
imaging biomarkers for genotype and hearing loss phenotype. We determine which …
imaging biomarkers for genotype and hearing loss phenotype. We determine which …
Prediction of Cochlear Implant Fitting by Machine Learning Techniques
H Koyama, A Kashio, T Yamasoba - Otology & Neurotology, 2023 - journals.lww.com
Objective This study aimed to evaluate the differences in electrically evoked compound
action potential (ECAP) thresholds and postoperative mapping current (T) levels between …
action potential (ECAP) thresholds and postoperative mapping current (T) levels between …
Leveraging real-world data to improve cochlear implant outcomes: Is the data available?
C Findlay, M Edwards, K Hough… - Cochlear Implants …, 2023 - Taylor & Francis
Objectives: A small but persistent proportion of individuals do not gain the expected benefit
from cochlear implants (CI). A step-change in the understanding of factors affecting …
from cochlear implants (CI). A step-change in the understanding of factors affecting …
Prognostic Modelling and Machine Learning in Cochlear Implantation
Healthcare professionals and researchers in the field of cochlear implantation should
continually strive to develop and clinically integrate novel research tools in order to improve …
continually strive to develop and clinically integrate novel research tools in order to improve …