A5101497161- Biomedical Text Mining and Ontologies
- Multiple Sclerosis Research Studies
- Topic Modeling
- Peripheral Neuropathies and Disorders
- Computational Drug Discovery Methods
- Systemic Lupus Erythematosus Research
- Natural Language Processing Techniques
- Urologic and reproductive health conditions
- Pharmacovigilance and Adverse Drug Reactions
- Ferroptosis and cancer prognosis
- Semantic Web and Ontologies
- Urological Disorders and Treatments
- Machine Learning in Healthcare
- Sexual function and dysfunction studies
- Petroleum Processing and Analysis
- Supercapacitor Materials and Fabrication
- Advancements in Battery Materials
- Sperm and Testicular Function
- Immunotherapy and Immune Responses
- Hormonal and reproductive studies
- Liver Disease Diagnosis and Treatment
- Genital Health and Disease
- Wildlife Ecology and Conservation
- Cancer, Lipids, and Metabolism
- Earthquake Detection and Analysis
Beijing Sport University
2025
The University of Texas Health Science Center at Houston
2014-2024
Xi'an Jiaotong University
2023-2024
Huawei Technologies (China)
2024
XinHua Hospital
2024
Shanxi Medical University
2018-2024
Xi'an University of Architecture and Technology
2024
Second Hospital of Shanxi Medical University
2022-2024
Peking University
2024
Third Affiliated Hospital of Sun Yat-sen University
2015-2023
The discovery of novel anticancer drugs is critical for the pharmaceutical research and development, patient treatment. Repurposing existing that may have unanticipated effects as potential candidates one way to meet this important goal. Systematic investigation efficient could provide valuable insights into trends in drugs, which contribute systematic new drugs. In study, we collected analyzed 150 approved by US Food Drug Administration (FDA). Based on drug mechanism action, these agents...
Abstract Objective This article presents our approaches to extraction of medications and associated adverse drug events (ADEs) from clinical documents, which is the second track 2018 National NLP Clinical Challenges (n2c2) shared task. Materials Methods The corpus used in this study was MIMIC-III database organizers annotated 303 documents for training 202 testing. Our system consists 2 components: a named entity recognition (NER) relation classification (RC) component. For each component,...
The COVID-19 pandemic swept across the world rapidly, infecting millions of people. An efficient tool that can accurately recognize important clinical concepts from free text in electronic health records (EHRs) will be valuable to accelerate research. To this end, study aims at adapting existing CLAMP natural language processing quickly build SignSym, which extract signs/symptoms and their 8 attributes (body location, severity, temporal expression, subject, condition, uncertainty, negation,...
Mining chemical-induced disease relations embedded in the vast biomedical literature could facilitate a wide range of computational applications, such as pharmacovigilance. The BioCreative V organized Chemical Disease Relation (CDR) Track regarding relation extraction from 2015. We participated all subtasks this challenge. In article, we present our participation system Extraction SysTem (CD-REST), an end-to-end for extracting literature. CD-REST consists two main components: (1) chemical...
The 2016 Clinical TempEval challenge addresses temporal information extraction from clinical notes.The is composed of six sub-tasks, each which to identify:(1) event mention spans, (2) time expression (3) attributes, (4) (5) events' relations the document creation times (DocTimeRel), and (6) narrative container among events times.In this article, we present an end-to-end system that all sub-tasks.Our achieved best performance for sub-tasks when plain texts were given as input.It also...
On December 18, 2023, a Ms 6.2 magnitude earthquake struck Jishishan, Gansu, China. The epicenter was located in the transition zone between Qinghai-Tibet Plateau and Loess Plateau, with maximum intensity of VIII, accompanied by numerous aftershocks. This resulted destruction collapse buildings caused casualties, as well multiple landslides other geological disasters. Additionally, triggered severe liquefied mudflow Zhongchuan Township, Gansu Province, burying 51 houses causing over 20...
Objective To evaluate the efficacy and safety of low-dose mycophenolate mofetil (MMF,1000 mg/day) treatment neuromyelitis optica spectrum disorders (NMOSDs). Methods This study was a multicenter, open, prospective, follow-up clinical trial. The data include retrospective from pretreatment phase prospective posttreatment phase. From September 2014 to February 2017, NMOSD patients seropositive for aquaporin 4-IgG (AQP4-IgG) were treated with MMF. Results Ninety MMF median duration 18 months...
Automated analysis of vaccine postmarketing surveillance narrative reports is important to understand the progression rare but severe adverse events (AEs). This study implemented and evaluated state-of-the-art deep learning algorithms for named entity recognition extract nervous system disorder-related from safety reports.We collected Guillain-Barré syndrome (GBS) related influenza Vaccine Adverse Event Reporting System (VAERS) 1990 2016. VAERS were selected manually annotated with major...
Medicinal chemistry patents contain rich information about chemical compounds. Although much effort has been devoted to extracting entities from scientific literature, limited numbers of patent mining systems are publically available, probably due the lack large manually annotated corpora. To accelerate development extraction for medicinal patents, 2015 BioCreative V challenge organized a track on Chemical and Drug Named Entity Recognition text (CHEMDNER patents). This included three...
Background: Myelin oligodendrocyte glycoprotein (MOG) antibody associated encephalomyelitis is increasingly being considered a distinct disease entity, with seizures and encephalopathy commonly reported. We investigated the clinical features of MOG-IgG positive patients presenting and/or in single cohort. Methods: Consecutive suspected idiopathic inflammatory demyelinating diseases were recruited from tertiary University hospital Guangdong province, China. Subjects seropositivity analyzed...
Myelin oligodendrocyte glycoprotein-associated disorders (MOGADs) are a rare new neurological autoimmune disease with unclear pathogenesis. Since linkage of the to human leucocyte antigen (HLA) has not been shown, we here investigated whether MOGAD is associated HLA locus.HLA genotypes 95 patients MOGADs, assessed between 2016 and 2018 from three academic centres, were compared 481 healthy Chinese Han individuals. Patients MOGADs included 51 paediatric-onset 44 adult-onset cases. All...
We investigated the serum neurofilament light chain (sNfL) and glial fibrillary acidic protein (sGFAP) levels in a cohort of Chinese patients with neuromyelitis optica spectrum disorders (NMOSD) multiple sclerosis (MS) relation to clinical disease course treatment. sNfL sGFAP were determined by ultrasensitive single molecule array (Simoa) assay NMOSD (n = 102) MS 98) healthy controls (HCs; n 84). Notably, 13 27 enrolled 1-year follow-up cohort. Levels compared data such as course, duration,...
ABSTRACT Background Initial insights into oncology clinical trial outcomes are often gleaned manually from conference abstracts. We aimed to develop an automated system extract safety and efficacy information study abstracts with high precision fine granularity, transforming them computable data for timely decision-making. Methods collected key conferences PubMed (2012-2023). The SEETrials was developed four modules: preprocessing, prompt modeling, knowledge ingestion postprocessing....
Information about drug–drug interactions (DDIs) supported by scientific evidence is crucial for establishing computational knowledge bases applications like pharmacovigilance. Since new reports of DDIs are rapidly accumulating in the literature, text-mining techniques automatic DDI extraction critical. We propose a novel approach automated pharmacokinetic (PK) detection that incorporates syntactic and semantic information into graph kernels, to address problem sparseness associated with...