Xuezhong Zhou

Xuezhong Zhou
Beijing Jiaotong University | NJTU · School of Computer and Information Technology

PhD

About

236
Publications
27,879
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
3,774
Citations
Introduction
clinical phenotype-genotype association, complex network, traditional Chinese medicine, data warehouse, clinical knowledge discovery
Additional affiliations
June 2016 - August 2020
The Hong Kong University of Science and Technology
Position
  • Visiting Scholar
January 2016 - February 2020
Brigham and Women's Hospital
Position
  • Visiting Schoolar
December 2015 - present
Beijing Jiaotong University
Position
  • Professor
Education
September 1999 - January 2005
Zhejiang University
Field of study
September 1995 - July 1999
Lanzhou University
Field of study
  • Computer Science

Publications

Publications (236)
Article
Full-text available
Biomedical named entity recognition (BioNER) from clinical texts is a fundamental task for clinical data analysis due to the availability of large volume of electronic medical record data, which are mostly in free text format, in real-world clinical settings. Clinical text data incorporates significant phenotypic medical entities (e.g., symptoms, d...
Article
Background: The coronavirus disease 2019 (COVID-19) spreads rapidly across the globe, seriously threatening the health of people all over the world. To reduce the diagnostic pressure of front-line doctors, an accurate and automatic lesion segmentation method is highly desirable in clinic practice. Purpose: Many proposed two-dimensional (2D) meth...
Article
Full-text available
Traditional Chinese medicine (TCM) has played an indispensable role in clinical diagnosis and treatment. Based on a patient’s symptom phenotypes, computation-based prescription recommendation methods can recommend personalized TCM prescription using machine learning and artificial intelligence technologies. However, owing to the complexity and indi...
Article
Full-text available
Due to the large-scale spread of COVID-19, which has a significant impact on human health and social economy, developing effective antiviral drugs for COVID-19 is vital to saving human lives. Various biomedical associations, e.g., drug-virus and viral protein-host protein interactions, can be used for building biomedical knowledge graphs. Based on...
Article
One of the most difficult problems that hinder the development and application of herbal medicine is how to illuminate the global effects of herbs on the human body. Currently, the chemo-centric network pharmacology methodology regards herbs as a mixture of chemical ingredients and constructs the 'herb-compound-target-disease' connections based on...
Conference Paper
Full-text available
Traditional Chinese medicine (TCM) has played an indispensable role in clinical diagnose and treatment. Based on patient’s symptom phenotypes, computation-based prescription recommendation methods can recommend personalized TCM prescription using machine learning and artificial intelligence technologies. However, owing to the complexity and individ...
Article
Full-text available
Symptom phenotypes have continuously been an important clinical entity for clinical diagnosis and management. However, non-specificity of symptom phenotypes for clinical diagnosis is one of the major challenges that need be addressed to advance symptom science and precision health. Network medicine has delivered a successful approach for understand...
Chapter
As a growing trend in current pharmacology research and an important medical application in network science research, network pharmacology has become an indispensable complement to traditional pharmacology research with the immense accumulation and integration of large-scale pharmacology and disease molecular network data. In addition to emerging n...
Article
Full-text available
The protein-protein interaction (PPI) networks can be regarded as powerful platforms to elucidate the principle and mechanism of cellular organization. Uncovering protein complexes from PPI networks will lead to a better understanding of the science of biological function in cellular systems. In recent decades, numerous computational algorithms hav...
Article
Introduction: Type 2 diabetes mellitus (T2DM) frequently associates with increasing multi-morbidity/treatment complexity. Some headway has been made to identify genetic and non-genetic risk factors for T2DM. However longitudinal clinical histories of individuals both before and after diagnosis of T2DM are likely to provide additional insight into...
Preprint
Full-text available
Introduction Type 2 diabetes mellitus (T2DM) frequently associates with increasing multi-morbidity/treatment complexity. Some headway has been made to identify genetic and non-genetic risk factors for T2DM. However longitudinal clinical histories of individuals both before and after diagnosis of T2DM are likely to provide additional insight into bo...
Article
Full-text available
Disease gene identification is a critical step towards uncovering the molecular mechanisms of diseases and systematically investigating complex disease phenotypes. Despite considerable efforts to develop powerful computing methods, candidate gene identification remains a severe challenge owing to the connectivity of an incomplete interactome networ...
Article
Chinese medicine (CM) was extensively used to treat COVID-19 in China. We aimed to evaluate the real-world effectiveness of add-on semi-individualized CM during the outbreak. A retrospective cohort of 1788 adult confirmed COVID-19 patients were recruited from 2235 consecutive linked records retrieved from five hospitals in Wuhan during 15 January t...
Article
Full-text available
As a well-established multidrug combinations schema, traditional Chinese medicine (herbal prescription) has been used for thousands of years in real-world clinical settings. This paper uses a complex network approach to investigate the regularities underlying multidrug combinations in herbal prescriptions. Using five collected large-scale real-worl...
Article
Full-text available
This study aims to explore the topological regularities of the character network of ancient traditional Chinese medicine (TCM) book. We applied the 2-gram model to construct language networks from ancient TCM books. Each text of the book was separated into sentences and a TCM book was generated as a directed network, in which nodes represent Chines...
Article
Full-text available
Coronavirus disease 2019 (COVID-19) is now pandemic worldwide and has heavily overloaded hospitals in Wuhan City, China during the time between late January and February. We reported the clinical features and therapeutic characteristics of moderate COVID-19 cases in Wuhan that were treated via the integration of traditional Chinese medicine (TCM) a...
Article
Full-text available
The knowledge of phenotype-genotype associations is crucial for the understanding of disease mechanisms. Numerous studies have focused on developing efficient and accurate computing approaches to predict disease genes. However, owing to the sparseness and complexity of medical data, developing an efficient deep neural network model to identify dise...
Article
Full-text available
This study investigated whether Panax notoginseng saponins (PNS) reduced atherosclerotic lesion formation in apolipoprotein E knockout (ApoE-KO) mice and illustrated the potential mechanism for a network pharmacology approach. Pharmacodynamics studies on ApoE-KO mice with atherosclerosis (AS) showed that PNS generated an obvious anti-AS action. The...
Article
Chinese medicine (CM) was extensively used to treat COVID-19 in China. We aimed to evaluate the real-world effectiveness of add-on semi-individualized CM during the outbreak. A retrospective cohort of 1788 adult confirmed COVID-19 patients were recruited from 2235 consecutive linked records retrieved from five hospitals in Wuhan during 15 January t...
Article
Full-text available
Background: Disease comorbidity is popular and has significant indications for disease progress and management. We aim to detect the general disease comorbidity patterns in Chinese populations using a large-scale clinical data set. Methods: We extracted the diseases from a large-scale anonymized data set derived from 8,572,137 inpatients in 453...
Article
Full-text available
Synonym mapping between phenotype concepts from different terminologies is difficult because terminology databases have been developed largely independently. Existing maps of synonymous phenotype concepts from different terminology databases are highly incomplete, and manually mapping is time consuming and laborious. Therefore, building an automati...
Preprint
UNSTRUCTURED Objective To predict the incidence of recurrent cardiovascular events in patients with stable coronary heart disease in one year, a simple and robust nomogram was established and validated. Method The predictive model was developed and validated in two prospective coronary artery disease cohorts. The total population was 3618, with 589...
Article
Full-text available
Pediatric cough is a heterogeneous condition in terms of symptoms and the underlying disease mechanisms. Symptom phenotypes hold complicated interactions between each other to form an intricate network structure. This study aims to investigate whether the network structure of pediatric cough symptoms is associated with the prognosis and outcome of...
Article
Full-text available
Unraveling protein functional modules from protein-protein interaction networks is a crucial step to better understand cellular mechanisms. In the past decades, numerous algorithms have been proposed to identify potential protein functional modules or complexes from protein-protein interaction (PPI) networks. Unfortunately, the number of PPIs is ra...
Article
Full-text available
Traditional Chinese Medicine (TCM) has received increasing attention as a complementary approach or alternative to modern medicine. However, experimental methods for identifying novel targets of TCM herbs heavily relied on the current available herb-compound-target relationships. In this work, we present an Herb-Target Interaction Network (HTINet)...
Article
Full-text available
Traditional Chinese Medicine (TCM) has received increasing attention as a complementary approach or alternative to modern medicine. However, experimental methods for identifying novel targets of TCM herbs heavily relied on the current available herb-compound-target relationships. In this work, we present an Herb-Target Interaction Network (HTINet)...
Article
Full-text available
Background Unplanned readmission within 31 days of discharge after stroke is a useful indicator for monitoring quality of hospital care. We evaluated the risk factors associated with 31-day unplanned readmission of stroke patients in China. Methods We identified 50,912 patients from 375 hospitals in 29 provinces, municipalities or autonomous distr...
Article
Full-text available
Recently, the pharmaceutical industry has heavily emphasized phenotypic drug discovery (PDD), which relies primarily on knowledge about phenotype changes associated with diseases. Traditional Chinese medicine (TCM) provides a massive amount of information on natural products and the clinical symptoms they are used to treat, which are the observable...
Article
Full-text available
Objective: Investigating the molecular mechanisms of symptoms is a vital task in precision medicine to refine disease taxonomy and improve the personalized management of chronic diseases. Although there are abundant experimental studies and computational efforts to obtain the candidate genes of diseases, the identification of symptom genes is rare...
Article
Full-text available
The discovery of disease-causing genes is a critical step towards understanding the nature of a disease and determining a possible cure for it. In recent years, many computational methods to identify disease genes have been proposed. However, making full use of disease-related (e.g., symptoms) and gene-related (e.g., Gene Ontology and proteinprotei...
Chapter
Full-text available
Background: Disease comorbidity is popular and has significant indications for disease progress and management. We aim to detect the general disease comorbidity patterns in Chinese populations using a large-scale clinical data set.
Article
Full-text available
Objectives: Network pharmacological methods were used to investigate the underlying molecular mechanisms of LianXia NingXin (LXNX) formula, a Chinese prescription, to treat coronary heart disease (CHD) and disease phenotypes (CHD related diseases and symptoms). Methods: The different seed gene lists associated with the herbs of LXNX formula, the CH...
Article
Full-text available
We present a study of electronic medical record (EMR) retrieval that emulates situations in which a doctor treats a new patient. Given a query consisting of a new patient's symptoms, the retrieval system returns the set of most relevant records of previously treated patients. However, due to semantic, functional, and treatment synonyms in medical t...
Data
The distribution on the number of genes of 1883 ICD diseases.
Data
The maximum betweenness (median) of ICD subcatagories.
Data
The diseases with significant higher edge density to the chapter than the average edge density of the diseases in the corresponding chapter.
Data
The significant modules in every NCDs.
Data
The disease association network of NC06M10.
Data
The overlapping and unique significant phenotypes among 296,487 and 480.
Data
The first-neighbor PPI subnetwork of the genes with 296, 487 and 480.
Data
The integrated disease network based on systematic integration process.