A difficulty-aware and task-augmentation method based on meta-learning model for few-shot diabetic retinopathy classification.

"Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-567/coif). Tuo Li and X.Z. are current employees of the Shandong Yunhai Guochuang Cloud Computing Equipment Industry Innovation Co., Ltd., Jinan, China. The other authors have no conflicts of interest to declare."

"Funding: This work was supported by the National Natural Science Foundation of China ( Nos. 61971271, 62201330, 62271294 ), the Shandong Province Science and Technology Small and Medium-Sized Enterprises Innovation Capacity Improvement Project ( No. 2022TSGC2017 ), the Shandong Province Major Technological Innovation Project ( Nos. 2022CXGC010502, 2022CXGC020507 ), and the Shandong Provincial Natural Science Foundation Major Basic Research Project ( No. ZR2022ZD16 )."