CDSS of Traditional Chinese Medicine Intervention for Dry Eye Syndrome

Construction and Evaluation of CDSS Based on AI of Traditional Chinese Medicine Intervention for Dry Eye Syndrome

This project is based on artificial intelligence (AI) algorithms to screen the effective methods of traditional Chinese medicine intervention for dry eye and its applicable conditions, and optimize the traditional Chinese medicine intervention plan for dry eye through the evaluation of evidence-based medicine and expert consensus, and construct the Clinical Decision support system of traditional Chinese medicine intervention for dry eye, secondly, a real-world prospective cohort study design is adopted, the CDSS system is used in the ophthalmology clinic, and its practical application effect on patients with dry eye is evaluated.

Dry eye is a common disease that affects tears and ocular surface. It can cause ocular surface discomfort, visual impairment and even blindness, affect the quality of life of patients and cause social and psychological harm. Interventions related to traditional Chinese medicine can effectively alleviate the clinical symptoms and signs of patients with dry eye, and are an indispensable part of the treatment of dry eye. However, at present, patients with dry eye are mainly diagnosed at the western medicine ophthalmology clinic. Due to the lack of knowledge of Chinese medicine by western medicine ophthalmologists, they are unable to provide patients with good guidance on Chinese medicine intervention measures, which may cause patients to miss Chinese medicine-related treatments. This project provides doctors of Western medicine with a clinical decision support system (CDSS) of Chinese medicine interventions for dry eye syndrome, so as to improve doctors' guidance and decision-making of Chinese medicine for patients. This project is based on artificial intelligence (AI) algorithms to screen the effective methods of traditional Chinese medicine intervention for dry eye and its applicable conditions, and optimize the traditional Chinese medicine intervention plan for dry eye through the evaluation of evidence-based medicine and expert consensus, and construct the Clinical Decision support system of traditional Chinese medicine intervention for dry eye, secondly, a real-world prospective cohort study design is adopted, the CDSS system is used in the ophthalmology clinic, and its practical application effect on patients with dry eye is evaluated.

Subjects' treatment regimens were influenced by the CDSS, which was the recommended system for Tradictional Chinese Medicine treatment of dry eye.

The treatment of the subjects was routine and not affected by the CDSS for Tradictional Chinese Medicine.

This project is based on the artificial intelligence (AI) algorithm to screen the effective methods of traditional Chinese medicine intervention for dry eye and its applicable conditions, and optimize the traditional Chinese medicine intervention plan for dry eye through the evaluation of evidence-based medicine and expert consensus, and construct the traditional Chinese medicine intervention Clinical Decision Support Systems (CDSS) for dry eye. At the same time, the CDSS is provided to clinicians for their selection.

Meibomian gland function score (MGFS) is used to evaluate the function of the meibomian glands and whether there is meibomian gland dysfunction.

Tear Meniscus Height (TMH) refers to the level of tear fluid at the junction of the light band on the surface of the cornea and conjunctiva and the light band on the lower eyelid margin.

Tear Break up time (TBUT) is usually used to diagnose dry eye syndrome. Diluted fluorescein sodium liquid is instilled into the conjunctival fornix of the lower eyelid, and the patient is instructed to blink and hold it, and start timing. The time when the first rupture spot appears is the tear film rupture time.

Inclusion Criteria: Ages 18 to 80 year-old. Meet the diagnostic criteria for dry eye, including ocular surface symptoms and signs. Exclusion Criteria: There are contradictions in diagnostic information, and the real condition of the disease is doubtful; The absence of necessary observation indicators; Lack of necessary prognostic information; The informed consent is not approved.

We are considering whether to share the data obtained from the study with the whole group of researchers, but the data to be Shared must be de-labeled data for the purpose of subject protection.