Attention-enhanced deep learning for cervical cytology: combining convolutional networks with multi-head attention and fuzzy logic

The method suggested herein has better noise robustness, interpretability through fuzzy logic, and automatic adaptation to various CNN frameworks without fine-tuning. These results acknowledge the promise of fuzzy logic-based CNN ensembles to improve machine-based cervical cancer diagnosis, which could be mapped to better and scalable diagnostic instruments in medical imaging.