AI Medical Compendium Topic:
Data Mining

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Biomedical event extraction based on GRU integrating attention mechanism.

BMC bioinformatics
BACKGROUND: Biomedical event extraction is a crucial task in biomedical text mining. As the primary forum for international evaluation of different biomedical event extraction technologies, BioNLP Shared Task represents a trend in biomedical text min...

Mining heterogeneous networks with topological features constructed from patient-contributed content for pharmacovigilance.

Artificial intelligence in medicine
Drug safety, also called pharmacovigilance, represents a serious health problem all over the world. Adverse drug reactions (ADRs) and drug-drug interactions (DDIs) are two important issues in pharmacovigilance, and how to detect drug safety signals h...

Data mining of the cancer-related lncRNAs GO terms and KEGG pathways by using mRMR method.

Mathematical biosciences
LncRNAs plays an important role in the regulation of gene expression. Identification of cancer-related lncRNAs GO terms and KEGG pathways is great helpful for revealing cancer-related functional biological processes. Therefore, in this study, we prop...

Conditional random fields for clinical named entity recognition: A comparative study using Korean clinical texts.

Computers in biology and medicine
BACKGROUND: This study demonstrates clinical named entity recognition (NER) methods on the clinical texts of rheumatism patients in South Korea. Despite the recent increase in the adoption rate of the electronic health record (EHR) system in global h...

RETRACTED: Diagnosis labeling with disease-specific characteristics mining.

Artificial intelligence in medicine
This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the authors; serious errors had been introd...

Normalizing Spontaneous Reports Into MedDRA: Some Experiments With MagiCoder.

IEEE journal of biomedical and health informatics
Text normalization into medical dictionaries is useful to support clinical tasks. A typical setting is pharmacovigilance (PV). The manual detection of suspected adverse drug reactions (ADRs) in narrative reports is time consuming and natural language...

Prioritising references for systematic reviews with RobotAnalyst: A user study.

Research synthesis methods
Screening references is a time-consuming step necessary for systematic reviews and guideline development. Previous studies have shown that human effort can be reduced by using machine learning software to prioritise large reference collections such t...

Mining features for biomedical data using clustering tree ensembles.

Journal of biomedical informatics
The volume of biomedical data available to the machine learning community grows very rapidly. A rational question is how informative these data really are or how discriminant the features describing the data instances are. Several biomedical datasets...

Automatic extraction of gene-disease associations from literature using joint ensemble learning.

PloS one
A wealth of knowledge concerning relations between genes and its associated diseases is present in biomedical literature. Mining these biological associations from literature can provide immense support to research ranging from drug-targetable pathwa...

Utilizing Big Data in Cancer Care.

Surgical oncology clinics of North America
Clinical research has boomed over the past decade, with the development of multiple clinical datasets that are available for retrospective review. However, data remain incomplete based on fragmented reporting, provider change, and loss of follow-up. ...