Enhancing dementia classification using denoising diffusion models and conditional deep convolutional neural networks

This study demonstrates the efficacy of DDM-generated synthetic datasets in improving dementia classification accuracy, setting a new benchmark for AI applications in healthcare. The proposed framework offers a scalable and robust solution for early diagnosis and treatment planning in dementia care.