Featured talks for the VCCA2020 conference

Twenty-five years of clinical data collection: from a single site relational database towards multi-site interoperability

Over the years Hannover Medical School has build a comprehensive data pool for patients with implantable hearing devices, which serves as a basis for answering various research questions and big data analyses.

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The HiGHmed approach for FAIR use of clinical and research data with openEHR – Focusing on interoperability

Patient-centric medical research benefits from the sharing and integration of complex and diverse data from different sources such as care, clinical research, and novel emerging data types.

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Learning from audiological data collected in the lab and the real world

Research in the last decades with the audiological data led to many important discoveries, and today, as the area of data emerges the focus turns to maturing those discoveries along the dimensions of coverage, applicability, bias, and privacy into solutions that improve the lives for people with hearing problems.

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Big Data and the Apple Hearing Study
Daily LEX8h over time in California, Florida, New York, and Texas.

Big Data and the Apple Hearing Study

The University of Michigan School of Public Health has partnered with Apple Inc. to use advances in smart device and wearable technology to evaluate the levels of sound at which iPhone users listen to music and other media, as well as how long and how often they listen.

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Can AI-led hearing healthcare address the growing global burden of hearing loss?

According to the recent WHO World Report on Hearing, there are approximately 500 million people worldwide with disabling hearing loss, the vast majority of whom receive no treatment. The consequences of this unmet need are dire: hearing loss is a top-5 contributor to the global burden of disability; the leading modifiable risk factor for dementia; and costs nearly 1 trillion dollars per year.

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Improving music enjoyment and speech-in-speech perception in cochlear implant users: a planned piano lesson intervention with a serious gaming control intervention

Although cochlear implants (CIs) provide hearing for severely-hearing-impaired or deaf populations, certain hearing abilities remain challenging for CI users.

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Computational audiology and the technical burden of machine learning

The biggest hurdle facing computational audiologists may not be perfecting machine learning methods, but creating the infrastructure- including hardware, data management tools, and software engineering skills- to support this new type of research.

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Dynamically Masked Audiograms with Machine Learning Audiometry
Final masked AMLAG results for one participant (127) with a left cochlear implant and no residual hearing. Red diamonds denote unheard tones and blue pluses denote heard tones. The most intense tones at lower frequencies in the left ear were effectively masked.

Dynamically Masked Audiograms with Machine Learning Audiometry

Dynamically masked audiograms achieve accurate true threshold estimates and reduce test time compared to current clinical masking procedures.

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