AI Medical Compendium Topic:
Data Mining

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Automatic classification of radiological reports for clinical care.

Artificial intelligence in medicine
Radiological reporting generates a large amount of free-text clinical narratives, a potentially valuable source of information for improving clinical care and supporting research. The use of automatic techniques to analyze such reports is necessary t...

Ontology-based literature mining and class effect analysis of adverse drug reactions associated with neuropathy-inducing drugs.

Journal of biomedical semantics
BACKGROUND: Adverse drug reactions (ADRs), also called as drug adverse events (AEs), are reported in the FDA drug labels; however, it is a big challenge to properly retrieve and analyze the ADRs and their potential relationships from textual data. Pr...

DeepText2GO: Improving large-scale protein function prediction with deep semantic text representation.

Methods (San Diego, Calif.)
As of April 2018, UniProtKB has collected more than 115 million protein sequences. Less than 0.15% of these proteins, however, have been associated with experimental GO annotations. As such, the use of automatic protein function prediction (AFP) to r...

Internet of Health Things: Toward intelligent vital signs monitoring in hospital wards.

Artificial intelligence in medicine
BACKGROUND: Large amounts of patient data are routinely manually collected in hospitals by using standalone medical devices, including vital signs. Such data is sometimes stored in spreadsheets, not forming part of patients' electronic health records...

Profiling Lung Cancer Patients Using Electronic Health Records.

Journal of medical systems
If Electronic Health Records contain a large amount of information about the patient's condition and response to treatment, which can potentially revolutionize the clinical practice, such information is seldom considered due to the complexity of its ...

MfeCNN: Mixture Feature Embedding Convolutional Neural Network for Data Mapping.

IEEE transactions on nanobioscience
Data mapping plays an important role in data integration and exchanges among institutions and organizations with different data standards. However, traditional rule-based approaches and machine learning methods fail to achieve satisfactory results fo...

Combining Context and Knowledge Representations for Chemical-Disease Relation Extraction.

IEEE/ACM transactions on computational biology and bioinformatics
Automatically extracting the relationships between chemicals and diseases is significantly important to various areas of biomedical research and health care. Biomedical experts have built many large-scale knowledge bases (KBs) to advance the developm...

Phrase mining of textual data to analyze extracellular matrix protein patterns across cardiovascular disease.

American journal of physiology. Heart and circulatory physiology
Extracellular matrix (ECM) proteins have been shown to play important roles regulating multiple biological processes in an array of organ systems, including the cardiovascular system. Using a novel bioinformatics text-mining tool, we studied six cate...

Simulation of patient flow in multiple healthcare units using process and data mining techniques for model identification.

Journal of biomedical informatics
INTRODUCTION: An approach to building a hybrid simulation of patient flow is introduced with a combination of data-driven methods for automation of model identification. The approach is described with a conceptual framework and basic methods for comb...