Sensorineural hearing impairment (SNHI) affects a significant proportion of children, with genetic factors playing a major role in over half of the cases (i.e., hereditary hearing impairment, HHI). Despite advances in genetic testing, over 40% of childhood SNHI cases remain undiagnosed due to limitations in investigating non-coding DNA regions and epigenetic factors. In addition, current inner ear imaging techniques lack automated tools for accurate diagnosis. This project aims to address these challenges by integrating computational genomics, deep learning, audiological data, and inner ear imaging to develop a comprehensive platform for diagnosing and deciphering HHI.
Project funding:
Interngovernmental programme administrated by Research Council of Lithuania: Lithuania– Taiwan
Project results:
This project seeks to provide a deeper understanding of the mechano-genetic basis of hereditary hearing impairment (HHI), while developing a transformative diagnostic tool for its early and accurate detection. By laying the foundation for future research in precision otology and advancing knowledge in computational genomics, deep learning, and inner ear imaging, it will strengthen the expertise of participating staff and foster interdisciplinary collaboration across these domains.
Period of project implementation: 2025-10-01 - 2027-09-30
Project coordinator: Kaunas University of Technology
