Extracting Medical Health Records in a Graph Based Approach
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

Research Paper | Computer Science & Engineering | India | Volume 5 Issue 8, August 2016

Extracting Medical Health Records in a Graph Based Approach

Dr. K. Nachimuthu

In this paper the study Overall health inspection is companion essential a part of care in several countries. Distinctive the participants in hazard are very important for early notice and preventive intervention. The fundamental challenge of learning a classification model for risk forecast lies within the unlabeled knowledge that establishes the bulk of the collected dataset. Theres no ground truth for discriminating their states of health. Significantly, the unlabeled knowledge describes the contributors in health investigations whose health conditions will vary greatly from healthy to very-ill. In this paper, we tend to recommend a graph-based, semi-supervised learning algorithmic rule mentioned to as SHG-Health (Semi-supervised Heterogeneous Graph on Health) for risk predictions to categorize an increasingly developing scenario with the bulk of the information unlabeled Wide-ranging experiments supported each real health examination datasets and artificial datasets are achieved to indicate the effectiveness and strength of our procedure. Associate economical repetitive algorithmic rule is projected and therefore the proof of conjunction is given.

Keywords: SHG-Health Semi-supervised Heterogeneous Graph on Health

Edition: Volume 5 Issue 8, August 2016

Pages: 903 - 904

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How to Cite this Article?

Dr. K. Nachimuthu, "Extracting Medical Health Records in a Graph Based Approach", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART20161005, Volume 5 Issue 8, August 2016, 903 - 904

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