GIST scientists advance voice pathology detection via adversarial continual learning
Dina Katabi, principal investigator for AI and health at the MIT Jameel Clinic, and Hong Kook Kim, professor at Gwangju Institute of Science and Technology (GIST) co-led a project to develop an adversarial task adaptive training approach that improves performance of a voice pathology detection (VPD) model by more than 15%, compared to the ResNet50 model. The development enables early and accurate diagnosis of voice-related disorders.
Hong states, “Our partnership with MIT has been instrumental in this success, facilitating ongoing exploration of contrastive learning. The collaboration is more than a mere partnership; it’s a fusion of minds and technologies that strive to reshape not only medical applications but various domains requiring intelligent, adaptive solutions.”