AIMC Topic: Data Mining

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Prediction of drug gene associations via ontological profile similarity with application to drug repositioning.

Methods (San Diego, Calif.)
The amount of biomedical literature has been increasing rapidly during the last decade. Text mining techniques can harness this large-scale data, shed light onto complex drug mechanisms, and extract relation information that can support computational...

Secondary use of electronic health records for building cohort studies through top-down information extraction.

Journal of biomedical informatics
Controlled clinical trials are usually supported with an in-front data aggregation system, which supports the storage of relevant information according to the trial context within a highly structured environment. In contrast to the documentation of c...

Secure Secondary Use of Clinical Data with Cloud-based NLP Services. Towards a Highly Scalable Research Infrastructure.

Methods of information in medicine
OBJECTIVES: The secondary use of clinical data provides large opportunities for clinical and translational research as well as quality assurance projects. For such purposes, it is necessary to provide a flexible and scalable infrastructure that is co...

Clinical time series prediction: Toward a hierarchical dynamical system framework.

Artificial intelligence in medicine
OBJECTIVE: Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventi...

Functional evaluation of out-of-the-box text-mining tools for data-mining tasks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The trade-off between the speed and simplicity of dictionary-based term recognition and the richer linguistic information provided by more advanced natural language processing (NLP) is an area of active discussion in clinical informatics. ...

A natural language processing pipeline for pairing measurements uniquely across free-text CT reports.

Journal of biomedical informatics
OBJECTIVE: To standardize and objectivize treatment response assessment in oncology, guidelines have been proposed that are driven by radiological measurements, which are typically communicated in free-text reports defying automated processing. We st...

Identification of the Best Anthropometric Predictors of Serum High- and Low-Density Lipoproteins Using Machine Learning.

IEEE journal of biomedical and health informatics
Serum high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol levels are associated with risk factors for various diseases and are related to anthropometric measures. However, controversy remains regarding the best anthropometric...

How to learn about gene function: text-mining or ontologies?

Methods (San Diego, Calif.)
As the amount of genome information increases rapidly, there is a correspondingly greater need for methods that provide accurate and automated annotation of gene function. For example, many high-throughput technologies--e.g., next-generation sequenci...

Electronic health record-enhanced signal detection using tree-based scan statistic methods.

American journal of epidemiology
Tree-based scan statistics (TBSS) are data mining methods that screen thousands of hierarchically related health outcomes to detect unsuspected adverse drug effects. TBSS traditionally analyze claims data with outcomes defined via diagnosis codes. TB...