AIMC Topic: Data Mining

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BelSmile: a biomedical semantic role labeling approach for extracting biological expression language from text.

Database : the journal of biological databases and curation
Biological expression language (BEL) is one of the most popular languages to represent the causal and correlative relationships among biological events. Automatically extracting and representing biomedical events using BEL can help biologists quickly...

Filtering large-scale event collections using a combination of supervised and unsupervised learning for event trigger classification.

Journal of biomedical semantics
BACKGROUND: Biomedical event extraction is one of the key tasks in biomedical text mining, supporting various applications such as database curation and hypothesis generation. Several systems, some of which have been applied at a large scale, have be...

Extracting a stroke phenotype risk factor from Veteran Health Administration clinical reports: an information content analysis.

Journal of biomedical semantics
BACKGROUND: In the United States, 795,000 people suffer strokes each year; 10-15 % of these strokes can be attributed to stenosis caused by plaque in the carotid artery, a major stroke phenotype risk factor. Studies comparing treatments for the manag...

Chemical entity recognition in patents by combining dictionary-based and statistical approaches.

Database : the journal of biological databases and curation
We describe the development of a chemical entity recognition system and its application in the CHEMDNER-patent track of BioCreative 2015. This community challenge includes a Chemical Entity Mention in Patents (CEMP) recognition task and a Chemical Pa...

miRiaD: A Text Mining Tool for Detecting Associations of microRNAs with Diseases.

Journal of biomedical semantics
BACKGROUND: MicroRNAs are increasingly being appreciated as critical players in human diseases, and questions concerning the role of microRNAs arise in many areas of biomedical research. There are several manually curated databases of microRNA-diseas...

A review of the applications of data mining and machine learning for the prediction of biomedical properties of nanoparticles.

Computer methods and programs in biomedicine
This article presents a comprehensive review of applications of data mining and machine learning for the prediction of biomedical properties of nanoparticles of medical interest. The papers reviewed here present the results of research using these te...

Detecting borderline infection in an automated monitoring system for healthcare-associated infection using fuzzy logic.

Artificial intelligence in medicine
BACKGROUND: Many electronic infection detection systems employ dichotomous classification methods, classifying patient data as pathological or normal with respect to one or several types of infection. An electronic monitoring and surveillance system ...

Text mining for precision medicine: automating disease-mutation relationship extraction from biomedical literature.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Identifying disease-mutation relationships is a significant challenge in the advancement of precision medicine. The aim of this work is to design a tool that automates the extraction of disease-related mutations from biomedical text to adv...

Active learning for ontological event extraction incorporating named entity recognition and unknown word handling.

Journal of biomedical semantics
BACKGROUND: Biomedical text mining may target various kinds of valuable information embedded in the literature, but a critical obstacle to the extension of the mining targets is the cost of manual construction of labeled data, which are required for ...