AIMC Topic: Data Mining

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Deep mining heterogeneous networks of biomedical linked data to predict novel drug-target associations.

Bioinformatics (Oxford, England)
MOTIVATION: A heterogeneous network topology possessing abundant interactions between biomedical entities has yet to be utilized in similarity-based methods for predicting drug-target associations based on the array of varying features of drugs and t...

DextMP: deep dive into text for predicting moonlighting proteins.

Bioinformatics (Oxford, England)
MOTIVATION: Moonlighting proteins (MPs) are an important class of proteins that perform more than one independent cellular function. MPs are gaining more attention in recent years as they are found to play important roles in various systems including...

Deep learning with word embeddings improves biomedical named entity recognition.

Bioinformatics (Oxford, England)
MOTIVATION: Text mining has become an important tool for biomedical research. The most fundamental text-mining task is the recognition of biomedical named entities (NER), such as genes, chemicals and diseases. Current NER methods rely on pre-defined ...

Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Recent progress in biosensor technology and wearable devices has created a formidable opportunity for remote healthcare monitoring systems as well as real-time diagnosis and disease prevention. The use of data mining techniques is indispensable for a...

nala: text mining natural language mutation mentions.

Bioinformatics (Oxford, England)
MOTIVATION: The extraction of sequence variants from the literature remains an important task. Existing methods primarily target standard (ST) mutation mentions (e.g. 'E6V'), leaving relevant mentions natural language (NL) largely untapped (e.g. 'glu...

Feasibility and Utility of Lexical Analysis for Occupational Health Text.

Journal of occupational and environmental medicine
OBJECTIVE: Assess feasibility and potential utility of natural language processing (NLP) for storing and analyzing occupational health data.

Screening Electronic Health Record-Related Patient Safety Reports Using Machine Learning.

Journal of patient safety
INTRODUCTION: The objective of this study was to develop a semiautomated approach to screening cases that describe hazards associated with the electronic health record (EHR) from a mandatory, population-based patient safety reporting system.

A New Essential Functions Installed DWH in Hospital Information System: Process Mining Techniques and Natural Language Processing.

Studies in health technology and informatics
Several kinds of event log data produced in daily clinical activities have yet to be used for secure and efficient improvement of hospital activities. Data Warehouse systems in Hospital Information Systems used for the analysis of structured data suc...