A personalized prediction model for urinary tract infections in type 2 diabetes mellitus using machine learning.

Patients with type 2 diabetes mellitus (T2DM) are at higher risk for urinary tract infections (UTIs), which greatly impacts their quality of life. Developing a risk prediction model to identify high-risk patients for UTIs in those with T2DM and assisting clinical decision-making can help reduce the incidence of UTIs in T2DM patients. To construct the predictive model, potential relevant variables were first selected from the reference literature, and then data was extracted from the Hospital Information System (HIS) of the Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital for analysis.

Develop an ADR prediction system of Chinese herbal injections containing Panax notoginseng saponin: a nested case-control study using machine learning.

Objective: This study aimed to develop an adverse drug reactions (ADR) antecedent prediction system using machine learning algorithms to provide the reference for security usage of Chinese herbal injections containing Panax notoginseng saponin in clinical practice.

Design: A nested case-control study.

Setting: National Center for ADR Monitoring and the Electronic Medical Record (EMR) system.

Predictive models of medication non-adherence risks of patients with T2D based on multiple machine learning algorithms.

Objective: Medication adherence plays a key role in type 2 diabetes (T2D) care. Identifying patients with high risks of non-compliance helps individualized management, especially for China, where medical resources are relatively insufficient. However, models with good predictive capabilities have not been studied.

Neuroprotective activity of two active chemical constituents from Tinospora hainanensis.

Objective: To determine the chemical structure of the new compound and investigate the protective effects of Tinosporaic acid A and B towards in-vitro neuro.

Methods: The structures of two new compounds were established by analyzing its 1D and 2D NMR spectra as well as HRESIMS. Their neuroprotective effects with respect to the antioxidant properties were evaluated by radical scavenging tests and hydrogen peroxide-injured oxidative stress model in PC12 cell lines.