Publications by authors named "Yixing Hu"
Article Synopsis
- A study aimed to identify a model predicting high bleeding risk for valve replacement patients on warfarin during hospitalization, focusing on patients with an INR ≥4.5.
- Researchers collected data from 2,376 cardiac valve replacement patients and used five machine-learning models, finding that the extreme gradient boosting (XGBoost) provided the best prediction accuracy.
- The successful model helps clinicians quickly identify high-risk patients and adapt treatment strategies to reduce the risk of bleeding during therapy.
Linezolid combined with rifampicin has shown excellent clinical outcomes against infection by multi-resistant Gram-positive bacteria. However, several studies have indicated that rifampicin reduces the plasma concentration of linezolid in patients with severe infection. Linezolid has been recommended for the treatment of patients with multidrug-resistant or extensively drug-resistant tuberculosis.
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- The study focused on predicting early neurologic deterioration (END) in patients with acute ischemic stroke (AIS) who underwent mechanical thrombectomy (MT), using various machine learning models.
- Among the models tested, XGBoost outperformed others with an area under the curve (AUC) of 0.826, indicating its strong predictive power.
- The findings suggest that an interpretable machine learning model can aid clinicians in assessing the risk of END, potentially improving decision-making for AIS patients during the perioperative period.
The unfavorable outcome of acute ischemic stroke (AIS) with large vessel occlusion (LVO) is related to clinical factors at multiple time points. However, predictive models used for dynamically predicting unfavorable outcomes using clinically relevant preoperative and postoperative time point variables have not been developed. Our goal was to develop a machine learning (ML) model for the dynamic prediction of unfavorable outcomes.
View Article and Find Full Text PDFChildhood brain tumors have suspected prenatal origins. To identify vulnerable developmental states, we generated a single-cell transcriptome atlas of >65,000 cells from embryonal pons and forebrain, two major tumor locations. We derived signatures for 191 distinct cell populations and defined the regional cellular diversity and differentiation dynamics.
View Article and Find Full Text PDF[The correlation of age with the risk of multiple organ dysfunction syndrome in the elderly patients with congestive heart failure and hypertension].
Zhongguo Ying Yong Sheng Li Xue Za Zhi
May 2012
Objective: To study the prediction value of age and congestive heart failure (CHF) for occurrence of multiple organ dysfunction syndrome elderly(MODSE) in old patients with hypertension.
Methods: Medical history of 19,996 cases (aged over 60 year) admitted to PLA General Hospital because of hypertension or developing hypertension during hospital stay from Jan 1993 to Dec 2008 were analyzed retrospectively. According to age the patients were divided into four groups: 60-69 year group; 70-79 year group; 80-89 year group; > or = 90 year older group.