Fig. 1. Architecture of the DeepDR-LLM system.

The DeepDR-LLM system consists of two modules: (1) module I (LLM module), which provides individualized management recommendations for patients with diabetes; (2) module II (DeepDR-Transformer module), which performs image quality assessment, DR lesion segmentation and DR/DME grading from standard or portable fundus images. There are two modes of integrating module I and module II in the DeepDR-LLM system. In the physician-involved integration mode, the outputs of module II (that is, fundus image gradability; the lesion segmentation of microaneurysm, cotton-wool spot, hard exudate and hemorrhage; DR grade; and DME grade) could assist physicians in generating DR/DME diagnosis results (that is, fundus image gradability, DR grade, DME grade and the presence of lesions). In the automated integration mode, the DR/DME diagnosis results include fundus image gradability, DR grade, DME grade classified by module II, and the presence of lesions segmented out by module II. These DR/DME diagnosis results and other clinical metadata will be fed into module I to generate individualized management recommendations for people with diabetes.