Multimodal sparse fusion transformer network with spatio-temporal decoupling for breast tumor classification

Key Points

• Breast tumor classification accuracy improved using a novel multimodal framework, enhancing diagnostic capabilities.
• Key evidence shows a classification accuracy of 92% across diverse datasets, highlighting significant potential in clinical settings.
• This analysis employed a spatio-temporal decoupling approach within a sparse fusion transformer network for effective data integration.
• Results support potential advancements in breast cancer diagnostics, emphasizing the need for further validation in diverse populations.