With the popularity and development of artificial intelligence (AI), disease screening systems based on AI algorithms are gradually emerging in the medical field. Such systems can be used for primary screening of diseases to relieve the pressure on primary health care. In recent years, AI algorithms have demonstrated good performance in the analysis and identification of lesion signs in the macular region of fundus color photography, and a screening system for fundus lesion signs applicable to primary screening is bound to emerge in the future. Therefore, to standardize the design and clinical application of the macular region lesion sign screening systems based on AI algorithms, the Ocular Fundus Diseases Group of Chinese Ophthalmological Society, in collaboration with relevant experts, has developed this guideline after investigating issues, discussing production evidence, and holding guideline workshops. This guideline aims to establish uniform standards for the definition of the macular region and lesion signs, AI adoption scenarios, algorithm model construction, datasets establishment and labeling, architecture and functions design, and image data acquisition for the screening system to guide the implementation of the screening work.