A5057297599- COVID-19 epidemiological studies
- Acute Kidney Injury Research
- Advanced Mathematical Modeling in Engineering
- Nonlinear Partial Differential Equations
- Sepsis Diagnosis and Treatment
- Geometric Analysis and Curvature Flows
- Stochastic processes and financial applications
- Cancer Immunotherapy and Biomarkers
- Machine Learning in Healthcare
- Data-Driven Disease Surveillance
- Geometry and complex manifolds
- Numerical methods in inverse problems
- Respiratory viral infections research
- Esophageal Cancer Research and Treatment
- Gastrointestinal Tumor Research and Treatment
- COVID-19 Pandemic Impacts
- Glaucoma and retinal disorders
- Colorectal Cancer Surgical Treatments
- Intestinal and Peritoneal Adhesions
- Respiratory Support and Mechanisms
- Lung Cancer Diagnosis and Treatment
- Sarcoma Diagnosis and Treatment
- Cardiac, Anesthesia and Surgical Outcomes
- Liver Disease Diagnosis and Treatment
- Immune cells in cancer
Hunan Children's Hospital
2018-2024
Central South University
2024
Beijing University of Chemical Technology
2023-2024
First Affiliated Hospital of Chengdu Medical College
2024
Chengdu Medical College
2024
Chinese Academy of Medical Sciences & Peking Union Medical College
2012-2023
Peking Union Medical College Hospital
2020-2023
Shanghai Normal University
2023
Wuhan University
2022
Renmin Hospital of Wuhan University
2022
Abstract We develop a health informatics toolbox that enables public workers to timely analyze and evaluate the time-course dynamics of novel coronavirus (COVID-19) infection using available data from China CDC. This is built upon hierarchical epidemiological model in which two observed time series daily proportions infected removed cases are emitted underlying governed by Markov SIR infectious disease process. extend incorporate various types time-varying quarantine protocols, including...
ABSTRACT Background With the outbreak of coronavirus disease 2019 (COVID-19), a sudden case increase in late February 2020 led to deep concern globally. Italy, South Korea, Iran, France, Germany, Spain, US and Japan are probably countries with most severe outbreaks. Collecting epidemiological data predicting epidemic trends important for development measurement public intervention strategies. Epidemic prediction results yielded by different mathematical models inconsistent; therefore, we...
We develop a health informatics toolbox that enables timely analysis and evaluation of the timecourse dynamics range infectious disease epidemics. As case study, we examine novel coronavirus (COVID-19) epidemic using publicly available data from China CDC. This is built upon hierarchical epidemiological model in which two observed time series daily proportions infected removed cases are generated underlying infection governed by Markov Susceptible-Infectious-Removed (SIR) process. extend SIR...
Understanding the transmission dynamics of COVID-19 is crucial for evaluating spread pattern it, especially in metropolitan areas China which may cause secondary outbreaks outside Wuhan, center new coronavirus disease outbreak. We used reported data from Jan 24, 2020, to Feb 23, fitted model infection, and on number cases estimate likely infections four high risk areas, as well facilitate understanding COVID-19's pattern. A group SERI statistical parameters were estimated using Markov Chain...
Abstract Background Although protective mechanical ventilation (MV) has been used in a variety of applications, lung injury may occur both patients with and without acute respiratory distress syndrome (ARDS). The purpose this study is to use machine learning identify clinical phenotypes for critically ill MV intensive care units (ICUs). Methods A retrospective cohort was conducted 5013 who had undergone treatment the Department Critical Care Medicine, Peking Union Medical College Hospital....
Heparin is one of the most commonly used medications in intensive care units. In clinical practice, use a weight-based heparin dosing nomogram standard practice for treatment thrombosis. Recently, machine learning techniques have dramatically improved ability computers to provide decision support and allowed possibility computer generated, algorithm-based recommendations.The objective this study was predict effects using methods optimize units based on predictions. Patient state predictions...
ABSTRACT Understanding the transmission dynamics of COVID-19 is crucial for evaluating its spread pattern, especially in metropolitan areas China, as can lead to secondary outbreaks outside Wuhan, center new coronavirus disease outbreak. In addition, experiences gained and lessons learned from China have potential provide evidence support other large cities with emerging cases. We used data reported January 24, 2020, February 23, fit a model infection, estimate likely number infections four...
There remains no optimal anticoagulation protocol for continuous renal replacement therapy (CRRT) with regional citrate (RCA) in pediatric patients elevated D-dimer levels. We aimed to assess the effects of different strategies on risk CRRT filter clotting these patients. Pediatric undergoing were retrospectively grouped based pre-CRRT levels and anticoagulant: D-RCA group (normal D-dimer, RCA only, n = 22), D+ (elevated 50), RCA+ systemic heparin (SHA) combined SHA, 55). The incidence...
Background Unfractionated heparin is widely used in the intensive care unit as an anticoagulant. However, weight-based dosing has been shown to be suboptimal and may place patients at unnecessary risk during their stay. Objective In this study, we intended develop validate a machine learning–based model predict treatment outcomes provide dosage recommendations clinicians. Methods A shallow neural network was adopted retrospective cohort of from Multiparameter Intelligent Monitoring Intensive...
Abstract Background Regional citrate anticoagulation (RCA) is an important local method during bedside continuous renal replacement therapy. To improve patient safety and achieve computer assisted dose monitoring control, we took intensive care units patients into cohort aiming at developing a data-driven machine learning model to give early warning of citric acid overdose provide adjustment suggestions on pumping rate 10% calcium gluconate input for RCA treatment. Methods Patient age,...
To investigate the efficacy and application value of plasma exchange as an adjuvant therapy in children with hemophagocytic syndrome (HPS).A prospective randomized controlled trial was designed. Forty severe HPS were enrolled, who treated pediatric intensive care unit (PICU) Hunan Children's Hospital from October 2018 to 2020. The randomly divided into a group conventional treatment using random number table, 20 each group. received etiological symptomatic supportive treatment, those...
Abstract Background The recombination-activating gene 1 (RAG1) protein is essential for the V (variable)-D (diversity)-J (joining) recombination process. Mutations in RAG1 have been reported to be associated with several types of immune disorders. Typical clinical features driven by variants include persistent infections, severe lymphopenia, and decreased immunoglobulin levels . Case presentation In this study, a 2-month-24-days-old infant recurrent fever was admitted our hospital multiple...
Let $(M,\omega)$ be a compact symplectic manifold. We denote by $\ac$ the space of all almost complex structure compatible with $\omega$. has natural foliation complexified orbit as leaf. obtain an explicit formula Hessian Hermitian Calabi functional at extremal K\"ahler metric in $\ac$. prove that is semi-positive definite critical point when restricted to orbit, corollaries we some results analogy case. also show weak parabolicity flow.
Publisher: School of Statistics, Renmin University China, Journal: Journal Data Science, Title: Rejoinder - An epidemiological forecast model and software assessing interventions on COVID-19 epidemic in Authors: Lili Wang, Yiwang Zhou, Jie He
A tandem ester hydrolysis/oxy–Cope rearrangement/methylation to divergently access the enantiomers of burchellin as well those its 1′-epi-diastereoisomer.