AI Medical Compendium Topic:
Data Mining

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DyKOSMap: A framework for mapping adaptation between biomedical knowledge organization systems.

Journal of biomedical informatics
BACKGROUND: Knowledge Organization Systems (KOS) and their associated mappings play a central role in several decision support systems. However, by virtue of knowledge evolution, KOS entities are modified over time, impacting mappings and potentially...

Non-redundant association rules between diseases and medications: an automated method for knowledge base construction.

BMC medical informatics and decision making
BACKGROUND: The widespread use of electronic health records (EHRs) has generated massive clinical data storage. Association rules mining is a feasible technique to convert this large amount of data into usable knowledge for clinical decision making, ...

SimConcept: a hybrid approach for simplifying composite named entities in biomedical text.

IEEE journal of biomedical and health informatics
One particular challenge in biomedical named entity recognition (NER) and normalization is the identification and resolution of composite named entities, where a single span refers to more than one concept (e.g., BRCA1/2). Previous NER and normalizat...

Using support vector machine ensembles for target audience classification on Twitter.

PloS one
The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential customers. In this paper, our aim is to investigate the use of both unsupervised and supervised learning...

Incorporating linguistic knowledge for learning distributed word representations.

PloS one
Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashio...

Multi-focus cluster labeling.

Journal of biomedical informatics
Document collections resulting from searches in the biomedical literature, for instance, in PubMed, are often so large that some organization of the returned information is necessary. Clustering is an efficient tool for organizing search results. To ...

Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Extracting medical knowledge from electronic medical records requires automated approaches to combat scalability limitations and selection biases. However, existing machine learning approaches are often regarded by clinicians as black boxe...

Using Ontology Fingerprints to disambiguate gene name entities in the biomedical literature.

Database : the journal of biological databases and curation
Ambiguous gene names in the biomedical literature are a barrier to accurate information extraction. To overcome this hurdle, we generated Ontology Fingerprints for selected genes that are relevant for personalized cancer therapy. These Ontology Finge...

Generating a focused view of disease ontology cancer terms for pan-cancer data integration and analysis.

Database : the journal of biological databases and curation
Bio-ontologies provide terminologies for the scientific community to describe biomedical entities in a standardized manner. There are multiple initiatives that are developing biomedical terminologies for the purpose of providing better annotation, da...

A semi-supervised learning framework for biomedical event extraction based on hidden topics.

Artificial intelligence in medicine
OBJECTIVES: Scientists have devoted decades of efforts to understanding the interaction between proteins or RNA production. The information might empower the current knowledge on drug reactions or the development of certain diseases. Nevertheless, du...