Predicting the hearing outcome in sudden sensorineural hearing loss via machine learning models
Clinical Otolaryngology2018Vol. 43(3), pp. 868–874
Citations Over TimeTop 10% of 2018 papers
Dan Bing, Jun Ying, Jianguo Miao, Liang Lan, D. Wang, Lidong Zhao, Z. Yin, Lan Yu, Jing Guan, Qingyu Wang
Abstract
With the input of enough features, DBN can be a robust prediction tool for SSHL. But LR is more practical for early prediction in routine clinical application using three readily available variables, that is time elapse between symptom onset and study entry, initial hearing level and audiogram.
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