Summary: Researchers in Portugal have developed AI models through the Audiology for All (A4A) project to predict hearing loss, offering tools to improve healthcare decision-making and accessibility.
Key Takeaways:
- AI-Powered Insights: The models identified a link between proximity to industrial areas and airports and a higher incidence of hearing loss, alongside socioeconomic factors limiting access to hearing aids.
- Healthcare Accessibility: Data visualizations and geographical analysis have guided targeted interventions, improving awareness and accessibility to hearing healthcare.
- Broader Applications: The project’s success paves the way for extending the methodology to other health screenings, such as diabetes and cardiovascular disease, in Portugal and beyond.
A team of researchers from the Department of Informatics Engineering (DEI) at the Faculty of Sciences and Technology of the University of Coimbra (FCTUC) in Portugal has developed a series of artificial intelligence (AI) models able to predict hearing loss, thus helping healthcare professionals in their decision-making process.
The Audiology for All (A4A) project, which aims to make hearing healthcare more accessible to all, was carried out in collaboration with the Coimbra School of Health Technology and the FCTUC’s Department of Electrical and Computer Engineering (DEEC). The project was led by Sensing Evolution (Evollu).
“We analyzed several existing databases to identify areas with the highest incidence of hearing loss and associated risk factors. One of the most striking findings was the link between proximity to industrial areas and airports and an increased prevalence of hearing loss. The study also revealed that lower levels of education and financial resources significantly impact the ability to purchase hearing aids, which are often unaffordable for low-income families,” says Nuno Lourenço, a lecturer at DEI and a researcher at the Centre for Informatics and Systems of the University of Coimbra (CISUC).
Alongside recommendation models for health professionals, “data visualizations were integrated to help people understand the importance of regular screening. The tool provided clear indications of geographical areas most prone to hearing problems and motivated targeted interventions such as screening campaigns in specific regions,” says the UC project coordinator.
The project using AI models to predict hearing loss has been very successful in expanding the database, and in providing accurate recommendations, despite the initial challenges posed by the COVID-19 pandemic, which limited the collection of representative samples. Its positive impact has led Sensing Evolution to consider extending the initiative to Spain and the UK.
“The next step will be to adapt the methodology developed to other types of screening, such as diabetes and cardiovascular disease, and to test the applicability of the models in other areas of preventive healthcare,” says Lourenço. “Although the algorithms need fine-tuning, the basic methodology is widely applicable, depending on the quality of available data.”
The A4A project aims to continue driving innovation in hearing healthcare, as well as in other areas of health screening in Portugal, and potentially worldwide.
Image: Dreamstime
link
