AIMC Topic:
Data Mining

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An Integrated Children Disease Prediction Tool within a Special Social Network.

Studies in health technology and informatics
This paper proposes a social network with an integrated children disease prediction system developed by the use of the specially designed Children General Disease Ontology (CGDO). This ontology consists of children diseases and their relationship wit...

Extracting Cross-Ontology Weighted Association Rules from Gene Ontology Annotations.

IEEE/ACM transactions on computational biology and bioinformatics
Gene Ontology (GO) is a structured repository of concepts (GO Terms) that are associated to one or more gene products through a process referred to as annotation. The analysis of annotated data is an important opportunity for bioinformatics. There ar...

Introducing Machine Learning Concepts with WEKA.

Methods in molecular biology (Clifton, N.J.)
This chapter presents an introduction to data mining with machine learning. It gives an overview of various types of machine learning, along with some examples. It explains how to download, install, and run the WEKA data mining toolkit on a simple da...

INSIGHTS FROM MACHINE-LEARNED DIET SUCCESS PREDICTION.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
To support people trying to lose weight and stay healthy, more and more fitness apps have sprung up including the ability to track both calories intake and expenditure. Users of such apps are part of a wider "quantified self" movement and many opt-in...

Natural Language Processing Technologies in Radiology Research and Clinical Applications.

Radiographics : a review publication of the Radiological Society of North America, Inc
The migration of imaging reports to electronic medical record systems holds great potential in terms of advancing radiology research and practice by leveraging the large volume of data continuously being updated, integrated, and shared. However, ther...

Active Batch Selection via Convex Relaxations with Guaranteed Solution Bounds.

IEEE transactions on pattern analysis and machine intelligence
Active learning techniques have gained popularity to reduce human effort in labeling data instances for inducing a classifier. When faced with large amounts of unlabeled data, such algorithms automatically identify the exemplar instances for manual a...