Diabetes prediction and drug administration using knowledge engineering approach

Knowledge Engineering (KE) has a place with all specialized, logical and social viewpoints associated with building, keeping up and utilizing information based frameworks. Machine learning when joined with Data mining procedures assumes a promising job in the subject of forecast. Information accessi...

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Bibliographic Details
Main Authors: Patil, Netra, Jayakumar, Naveenkumar, Patil, Sheetal S., Pawar, Avinash M., Kadam, Amol
Format: Conference Proceeding
Language:English
Subjects:
Data mining
Diabetes
Health services
Knowledge engineering
Machine learning
Software engineering
Online Access:Get full text
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Summary:Knowledge Engineering (KE) has a place with all specialized, logical and social viewpoints associated with building, keeping up and utilizing information based frameworks. Machine learning when joined with Data mining procedures assumes a promising job in the subject of forecast. Information accessibility is enormous in medical services, as is the requirement to extract data from it for improved forecasting, conclusion, therapyand medication innovation. The study concentrated on the location and prediction of Type – II Diabetes, which is considered one among the world’s fastest growing degenerative illnesses, in accordance withWHO in 2014. Diabetes Type IIis among the several common diseases with long-term consequences and a large number of medical complications. Diabetes, if it is not treated and undetected, may result in a slew of issues. Early Diabetic detection is critical for timely treatment, which can prevent the disease from progressing to a more serious stage. The work consists of a way for identifying and predicting diabetic health conditions to be able deliver the prescribed drugs.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0157085