HHO optimized support vector machine classifier for traditional Chinese medicine syndrome differentiation of diabetic retinopathy.

Aim: To develop a classifier for traditional Chinese medicine (TCM) syndrome differentiation of diabetic retinopathy (DR), using optimized machine learning algorithms, which can provide the basis for TCM objective and intelligent syndrome differentiation.

Methods: Collated data on real-world DR cases were collected. A variety of machine learning methods were used to construct TCM syndrome classification model, and the best performance was selected as the basic model.

[Temporal and spatial evolution of ecosystem service value in Ili Valley and its driving factors].

Ili Valley is an important ecological barrier in western China and an important economic zone of the Belt and Road Initiative. Exploring the driving factors of ecosystem service value (ESV) based on land use change is of great significance for optimizing regional ecological environment and coordinating human-land relationship. Based on three periods of land use data from 2000 to 2020 in Yili Valley, we used ArcGIS 10.

[Changes in the hemodynamic parameters of the portal vein and serum fibrosis markers in patients with chronic viral hepatitis B].

Objective: To explore the relationship between portal vein hemodynamics and the severity of fibrosis in patients with chronic hepatitis.

Methods: Portal vein blood flow velocity (PBFVe) and volume (PBFVo) along with the serum fibrosis markers were examined in 71 patients with chronic viral hepatitis B, and hepatic pathological changes were routinely observed.

Results: As the hepatitis progressed, the PBFVe decreased in close inverse relation to the degree of liver fibrosis (P<0.