Publications by authors named "PeiYang Wang"
Article Synopsis
- The study investigates the link between oxidative stress and bone mineral density (BMD) in adults under 40, focusing on how an oxidative balance score (OBS) could affect the risk of osteopenia.
- Using data from over 3,900 participants in the NHANES survey, researchers applied statistical analyses to evaluate the correlation between dietary/lifestyle factors and BMD.
- The results indicate that higher OBS is associated with a significantly lower risk of osteopenia, suggesting that adopting an antioxidant-rich diet and lifestyle could help maintain bone health in young adults.
Article Synopsis
- This study aimed to create and test a machine learning framework to predict cerebrospinal fluid leakage (CSFL) in lumbar fusion surgery, highlighting the need for better postoperative complication predictions due to rising spinal surgeries.
- The researchers analyzed clinical and imaging data from 3505 patients, experimenting with six different machine learning models, with XGBoost providing the best predictive accuracy.
- Key risk factors for CSFL were identified through SHAP analysis, including various anatomical measurements and surgical details, demonstrating the model's applicability in real clinical settings.
Article Synopsis
- The objective of the study was to create and validate AI models using natural language processing to diagnose lumbar disc herniation (LDH) with L5 and S1 radiculopathy, based on electronic health records (EHRs).
- The research involved analyzing EHRs from patients who underwent specific surgeries between 2013 and 2021, focusing on nurse documentation related to nerve root compression to train machine learning models.
- Results showed that the long short-term memory model achieved the highest performance metrics in identifying L5 and S1 radiculopathy, suggesting that AI analysis of EHRs could significantly improve diagnostic processes for lumbar diseases.
Identification of lncRNA-based regulatory mechanisms of Takifugu rubripes growth traits in fast and slow-growing family lines.
Comp Biochem Physiol Part D Genomics Proteomics
March 2024
Family selection is an important method in fish aquaculture because growth is the most important economic trait. Fast-and slow-growing families of tiger puffer fish (Takifugu rubripes) have been established through family selection. The development of teleost fish is primarily controlled by the growth hormone (GH)-insulin-like growth factor 1 (IGF-1) axis that includes the hypothalamus-pituitary-liver.
View Article and Find Full Text PDFStudy Design: Retrospective study.
Objectives: Our objective is to create comprehensible machine learning (ML) models that can forecast bone cement leakage in percutaneous vertebral augmentation (PVA) for individuals with osteoporotic vertebral compression fracture (OVCF) while also identifying the associated risk factors.
Methods: We incorporated data from patients (n = 425) which underwent PVA.
Article Synopsis
- The study is a retrospective analysis involving 1159 patients who underwent percutaneous endoscopic lumbar discectomy (PELD) for lumbar disc herniation (LDH) between July 2014 and December 2019, aiming to predict recurrent lumbar disc herniation (rLDH) using machine learning models.
- Significant factors influencing rLDH included body mass index (BMI), facet orientation, herniation type, Modic changes, and disc calcification, with various machine learning models, such as Extreme Gradient Boost (XGBoost) and Random Forest, showing strong predictive performance.
- The findings suggest that using these machine learning models could improve decision-making and potentially reduce rLDH rates after PELD
Article Synopsis
- - The study aimed to create machine learning algorithms using natural language processing (NLP) to automatically distinguish between lumbar disc herniation (LDH) and lumbar spinal stenosis (LSS) from admission notes that describe symptoms.
- - Data from 1921 patients was analyzed using two models: Long Short-Term Memory (LSTM) and extreme gradient boosting (XGBoost), with performance measured using various metrics.
- - Results showed that the LSTM model outperformed the XGBoost model in accuracy and recall, indicating that NLP-based algorithms could effectively aid in diagnosing spine diseases, particularly in differentiating between LDH and LSS.
Study Design: Narrative review.
Objectives: This review aims to present current applications of machine learning (ML) in spine domain to clinicians.
Methods: We conducted a comprehensive PubMed search of peer-reviewed articles that were published between 2006 and 2020 using terms (spine, spinal, lumbar, cervical, thoracic, machine learning) to examine ML in spine.
[Study of modified subcutaneous lumbar spine index as a predictor for short-term effectiveness in transforaminal lumbar interbody fusion].
Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi
July 2021
Objective: To explore the value of modified subcutaneous lumbar spine index (MSLSI) as a predictor for short-term effectiveness of transforaminal lumbar interbody fusion (TLIF) in treatment of lumbar degenerative disease (LDD).
Methods: Between February 2014 and October 2019, 450 patients who were diagnosed as LDD and received single-segment TLIF were included in the study. Based on the MSLSI measured by preoperative lumbar MRI, the patients were sorted from small to large and divided into three groups ( =150).
(1) Background: Rhubarb anthraquinones-a class of components with neuroprotective function-can be used to alleviate cerebral ischemia reperfusion injury. (2) Methods: The three pharmacodynamic indicators are neurological function score, brain water content, and cerebral infarction area; UPLC-MS/MS was used in pharmacokinetic studies to detect plasma concentrations at different time points, and DAS software was used to calculate pharmacokinetic parameters in a noncompartmental model. (3) Results: The results showed that the pharmacodynamics and pharmacokinetics of one of the five anthraquinone aglycones could be modified by the other four anthraquinones, and the degree of interaction between different anthraquinones was different.
View Article and Find Full Text PDFObjectives: The aim of this study was to evaluate the impact of HIV and sexually transmitted disease (STD) prevention interventions among female sex workers (FSWs) in the city of Hohhot in northern China.
Methods: Three serial cross-sectional surveys were conducted in 2006, 2007, and 2008 among FSWs. A questionnaire was administered to the FSWs, and HIV and syphilis tests were performed for all participants.