AIMC Topic: Data Mining

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Identifying Chemical-Disease Relationship in Biomedical Text Using a Multiple Kernel Learning-Boosting Method.

Studies in health technology and informatics
Chemical-induced disease relations (CID) are crucial in various biomedical tasks. In the CID task of Biocreative V, no classifiers with multiple kernels have been developed. In this study, a multiple kernel learning-boosting (MKLB) method is proposed...

Identifying Patients' Smoking Status from Electronic Dental Records Data.

Studies in health technology and informatics
Smoking is a significant risk factor for initiation and progression of oral diseases. A patient's current smoking status and tobacco dependency can aid clinical decision making and treatment planning. The free-text nature of this data limits accessib...

A Semi-Automatic Framework to Identify Abnormal States in EHR Narratives.

Studies in health technology and informatics
Disease ontology, defined as a causal chain of abnormal states, is believed to be a valuable knowledge base in medical information systems. Automatic mapping between electronic health records (EHR) and disease ontology is indispensable for applying d...

"Hybrid Topics" - Facilitating the Interpretation of Topics Through the Addition of MeSH Descriptors to Bags of Words.

Studies in health technology and informatics
Extracting and understanding information, themes and relationships from large collections of documents is an important task for biomedical researchers. Latent Dirichlet Allocation is an unsupervised topic modeling technique using the bag-of-words ass...

General Symptom Extraction from VA Electronic Medical Notes.

Studies in health technology and informatics
There is need for cataloging signs and symptoms, but not all are documented in structured data. The text from clinical records are an additional source of signs and symptoms. We describe a Natural Language Processing (NLP) technique to identify sympt...

Translational Morphosyntax: Distribution of Negation in Clinical Records and Biomedical Journal Articles.

Studies in health technology and informatics
Prior knowledge of the distributional characteristics of linguistic phenomena can be useful for a variety of language processing tasks. This paper describes the distribution of negation in two types of biomedical texts: scientific journal articles an...

Decision Support Systems in Health Care - Velocity of Apriori Algorithm.

Studies in health technology and informatics
The amount of stored data in health information systems can reach tera- and petabytes and application of specific algorithms in the field of data mining makes finding useful information suitable for making quality business decisions. A frequently use...

Exploring convolutional neural networks for drug-drug interaction extraction.

Database : the journal of biological databases and curation
Drug-drug interaction (DDI), which is a specific type of adverse drug reaction, occurs when a drug influences the level or activity of another drug. Natural language processing techniques can provide health-care professionals with a novel way of redu...

Machine Learning Techniques in Exploring MicroRNA Gene Discovery, Targets, and Functions.

Methods in molecular biology (Clifton, N.J.)
In recent years, the role of miRNAs in post-transcriptional gene regulation has provided new insights into the understanding of several types of cancers and neurological disorders. Although miRNA research has gathered great momentum since its discove...

Acronym Disambiguation in Spanish Electronic Health Narratives Using Machine Learning Techniques.

Studies in health technology and informatics
Electronic Health Records (EHRs) are now being massively used in hospitals what has motivated current developments of new methods to process clinical narratives (unstructured data) making it possible to perform context-based searches. Current approac...