Johan Flyborg and I had the honor of presenting our research at the International Conference on Bioinformatics and Computational Biology (ICBCB) 2024 in Tokyo. Our study, “Oral Health Parameter-Based Mini-Mental State Examination (Score) Indication Using Machine Learning,” represents a collaborative effort to explore the intersection of oral health and cognitive function through the lens of machine learning.
In this work, we applied advanced machine learning algorithms to oral health parameters in an effort to estimate Mini-Mental State Examination (MMSE) scores. Our goal was to create a novel, non-invasive approach for early detection of cognitive impairment—one that could potentially support earlier interventions and improve patient outcomes.
This research brought together elements of bioinformatics, computational biology, dentistry, and neurology, and we’re proud to contribute to a growing body of interdisciplinary work aimed at tackling complex healthcare challenges.
Presenting our findings to an international audience of experts was an incredible experience, and we were grateful for the recognition and feedback we received. We’re excited to continue building on this foundation and explore the broader potential of technology-driven health innovations.