Development of a deep learning model using multimodal data for dementia diagnosis

The multimodal deep learning model combining voice, drawing, and clinical data demonstrated promising performance in diagnosing cognitive impairment and dementia. These findings suggest that integrating diverse data modalities can enhance diagnostic accuracy and provide a scalable approach for early detection in clinical and real-world settings.