An Algorithm for Health Informatics Based on Extreme Machine Learning

SHARAD GARG; CHANDRA SHEKHAR YADAV; AREEBA KAZIM

An Algorithm for Health Informatics Based on Extreme Machine Learning

Authors: SHARAD GARG, CHANDRA SHEKHAR YADAV, AREEBA KAZIM

Unique Paper ID: 155377
Volume: 8
Issue: 10
PageNo: 73-77

Keywords: dataset health machine learning

Abstract:
Health-care organisations may foresee patterns in a patient's medical condition and behaviour by using data mining, which entails examining several options and establishing connections between apparently unrelated bits of information. The volume and variety of raw data generated by healthcare institutions make it difficult to make sense of everything. Data must be collected and stored in an organised manner, as well as integrated, in order to develop a unified medical information system. In health, data mining permits the examination of a diverse set of data models that are unavailable or obscured by conventional analytical techniques. The objective of this research is to take a diabetic health dataset and analyse it using machine learning techniques to increase diabetes prediction accuracy.

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Cite This Article

ISSN: 2349-6002
Volume: 8
Issue: 10
PageNo: 73-77

An Algorithm for Health Informatics Based on Extreme Machine Learning

Available:https://ijirt.org/Article?manuscript=155377

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