Intelligent Identification of Cerebrospinal Fluid for the Diagnosis of Parkinson's Disease.

Cerebrospinal fluid (CSF) biomarkers are more sensitive than the Movement Disorder Society (MDS) criteria for detecting prodromal Parkinson's disease (PD). Early detection of PD provides the best chance for successful implementation of disease-modifying treatments, making it crucial to effectively identify CSF extracted from PD patients or normal individuals. In this study, an intelligent sensor array was built by using three metal-organic frameworks (MOFs) that exhibited varying catalytic kinetics after reacting with potential protein markers.

RegEMR: a natural language processing system to automatically identify premature ovarian decline from Chinese electronic medical records.

Background: The ovarian reserve is a reservoir for reproductive potential. In clinical practice, early detection and treatment of premature ovarian decline characterized by abnormal ovarian reserve tests is regarded as a critical measure to prevent infertility. However, the relevant data are typically stored in an unstructured format in a hospital's electronic medical record (EMR) system, and their retrieval requires tedious manual abstraction by domain experts.

Intelligent Clinical Lab for the Diagnosis of Post-Neurosurgical Meningitis Based on Machine-Learning-Aided Cerebrospinal Fluid Analysis.

Post-neurosurgical meningitis (PNM) often leads to serious consequences; unfortunately, the commonly used clinical diagnostic methods of PNM are time-consuming or have low specificity. To realize the accurate and convenient diagnosis of PNM, herein, we propose a comprehensive strategy for cerebrospinal fluid (CSF) analysis based on a machine-learning-aided cross-reactive sensing array. The sensing array involves three Eu-doped metal-organic frameworks (MOFs), which can generate specific fluorescence responding patterns after reacting with potential targets in CSF.

[Characteristics of death cases caused by road traffic accident in Shenzhen].

Objective: By summarize the characteristics of death cases caused by road traffic accident, to provide information and data for prevention of traffic accident.

Methods: To retrospectively analyze 4148 death cases caused by road traffic accident in Shenzhen. The characteristics studied include the age and sex of the dead, the cause of death, time and place of the accidents and vehicle types, etc.