Auditory biomarkers and AI as the new intelligence of auditory sciences

Artificial intelligence has profoundly transformed diagnostic medicine over the past decades. Its impact has been remarkable in various therapeutic areas - ophthalmology, cardiology, neurology... - thanks to the use of technologies - ultrasound, imaging, tomography...Inspired by the visual system and fueled by the proliferation of big data and machine learning, computational audiology has also experienced significant growth over the last decade.

I am proud to say that Cilcare has distinguished itself in recent years by using digital data and AI for effective and non-invasive solutions applied to auditory data analysis. This expertise allows us to guide our clinical development strategies in an unique and unprecedented way.

So what do we lack now? Adequate recognition of auditory sciences for the preventive medicine of tomorrow!

Hearing, an open door to overall health.

Today, scientific advances converge towards an integrated vision of health, where every aspect of human well-being is scrutinized with precision. In the current medical landscape, hearing is often underestimated, despite its crucial importance for overall health. Yet, with the progress of biotechnology, pharmacology, and AI, it is essential to integrate auditory biomarkers to preserve health and prevent serious diseases. These biological indicators offer a unique insight into human health, ranging from auditory thresholds to auditory evoked potentials, revealing connections with neurological and neuropsychiatric conditions such as Alzheimer's disease, Parkinson's disease, or even diabetes - diabetic individuals are twice more likely to suffer from hearing disorders. This neglect of auditory health in medical monitoring often leaves symptoms unexplained, highlighting a gap to be filled.

Auditory biomarkers and AI, a precise window to preventive medicine?

By combining auditory data with artificial intelligence, we can also anticipate hearing disorders and detect hidden conditions earlier. Sophisticated predictive models can be developed to anticipate the progression of hearing disorders in individuals, thus allowing early intervention and more effective treatments. Similarly, AI can help identify subtle patterns in auditory physiological data, revealing hidden auditory conditions even before the onset of obvious symptoms.

For example, hidden hearing loss, difficult to diagnose with standard tests, is often caused by abnormalities in sound nerve transmission, such as synaptopathy. It is estimated that between 10% and 15% of patients with hearing loss do not receive a clear diagnosis. By integrating imaging techniques such as electrophysiology, a complete view of the auditory system could be obtained, revealing correlations with synaptopathy. AI algorithms could be used to analyze this data and identify patterns associated with synaptopathy, allowing for precise evaluation and standard creation. And this would clearly enable audiologists to spot signs of synaptopathy in individuals!

At Cilcare, we are into it, investing in several research projects to define auditory signatures specific to synaptopathy, crucial for the development of precise diagnostics and tailored treatments.

An urgent need to place hearing on par with other senses

We have thus made a leap forward in auditory sciences, there is no denying that. But if we truly want to revolutionize the medicine of tomorrow, it seems to me that a clear and systematic vision is necessary. Governments must recognize the importance of hearing for health and promote its integration into care pathways from a young age.

This requires a paradigm shift, where hearing is considered a full-fledged medical biomarker, scrutinized and evaluated throughout life.

This requires collective commitment to rethink our approaches to health and embrace a more inclusive vision, where each sense is recognized as a fundamental pillar of human well-being.