Robust Data-Driven Auditory Profiling Towards Precision Audiology

Data-Driven Proficiency Profiling

Deep Thought is a logic tutor where students practice constructing deductive logic proofs. Within Deep Thought is a data-driven mastery learning system (DDML), which calculates student proficiency based on rule scores weighted by expert-decided weights in order to assign problem sets of appropriate difficulty. In this study, we designed and tested a data-driven proficiency profiler (DDPP) metho...

Data-driven robust optimization

The last decade witnessed an explosion in the availability of data for operations research applications. Motivated by this growing availability, we propose a novel schema for utilizing data to design uncertainty sets for robust optimization using statistical hypothesis tests. The approach is flexible and widely applicable, and robust optimization problems built from our new sets are computation...

Auditory steady state response in pediatric audiology.

UNLABELLED The main issue regarding pediatric audiology diagnosis is determining procedures to configure reliable results which can be used to predict frequency-specific hearing thresholds. AIM To investigate the correlation between auditory steady-state response (ASSR) with other tests in children with sensorineural hearing loss. METHODS Prospective cross-sectional contemporary cohort stud...

Auditory brainstem response in paediatric audiology.

Clustering Audiology Data

In this paper we describe new results of statistical and neural data mining of audiology patient records, with the ultimate aim of looking for factors influencing which patients would most benefit from being fitted with a hearing aid. We describe how a combination of neural and statistical techniques can usefully subdivide a set of patients into clusters, based on their hearing thresholds at si...