AI Medical Compendium Topic:
Data Mining

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Canary: An NLP Platform for Clinicians and Researchers.

Applied clinical informatics
Information Extraction methods can help discover critical knowledge buried in the vast repositories of unstructured clinical data. However, these methods are underutilized in clinical research, potentially due to the absence of free software geared t...

A Novel Continuous Blood Pressure Estimation Approach Based on Data Mining Techniques.

IEEE journal of biomedical and health informatics
Continuous blood pressure (BP) estimation using pulse transit time (PTT) is a promising method for unobtrusive BP measurement. However, the accuracy of this approach must be improved for it to be viable for a wide range of applications. This study pr...

Deep image mining for diabetic retinopathy screening.

Medical image analysis
Deep learning is quickly becoming the leading methodology for medical image analysis. Given a large medical archive, where each image is associated with a diagnosis, efficient pathology detectors or classifiers can be trained with virtually no expert...

Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods.

Artificial intelligence in medicine
BACKGROUND AND OBJECTIVES: Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE fram...

Using classification models for the generation of disease-specific medications from biomedical literature and clinical data repository.

Journal of biomedical informatics
OBJECTIVE: Mining disease-specific associations from existing knowledge resources can be useful for building disease-specific ontologies and supporting knowledge-based applications. Many association mining techniques have been exploited. However, the...

Learning from biomedical linked data to suggest valid pharmacogenes.

Journal of biomedical semantics
BACKGROUND: A standard task in pharmacogenomics research is identifying genes that may be involved in drug response variability, i.e., pharmacogenes. Because genomic experiments tended to generate many false positives, computational approaches based ...

Novelty Indicator for Enhanced Prioritization of Predicted Gene Ontology Annotations.

IEEE/ACM transactions on computational biology and bioinformatics
Biomolecular controlled annotations have become pivotal in computational biology, because they allow scientists to analyze large amounts of biological data to better understand test results, and to infer new knowledge. Yet, biomolecular annotation da...

Building a comprehensive syntactic and semantic corpus of Chinese clinical texts.

Journal of biomedical informatics
OBJECTIVE: To build a comprehensive corpus covering syntactic and semantic annotations of Chinese clinical texts with corresponding annotation guidelines and methods as well as to develop tools trained on the annotated corpus, which supplies baseline...

DES-ncRNA: A knowledgebase for exploring information about human micro and long noncoding RNAs based on literature-mining.

RNA biology
Noncoding RNAs (ncRNAs), particularly microRNAs (miRNAs) and long ncRNAs (lncRNAs), are important players in diseases and emerge as novel drug targets. Thus, unraveling the relationships between ncRNAs and other biomedical entities in cells are criti...