Matches in SemOpenAlex for { <https://semopenalex.org/work/W2970642414> ?p ?o ?g. }
Showing items 1 to 79 of
79
with 100 items per page.
- W2970642414 abstract "The diabetes is one of lethal diseases in the world. It is additional a inventor of various varieties of disorders foe example: coronary failure, blindness, urinary organ diseases etc. In such case the patient is required to visit a diagnostic center, to get their reports after consultation. Due to every time they have to invest their time and currency. But with the growth of Machine Learning methods we have got the flexibility to search out an answer to the current issue, we have got advanced system mistreatment information processing that has the ability to forecast whether the patient has polygenic illness or not. Furthermore, forecasting the sickness initially ends up in providing the patients before it begins vital. Information withdrawal has the flexibility to remove unseen data from a large quantity of diabetes associated information. The aim of this analysis is to develop a system which might predict the diabetic risk level of a patient with a better accuracy. Model development is based on categorization methods as Decision Tree, ANN, Naive Bayes and SVM algorithms. For Decision Tree, the models give precisions of 85%, for Naive Bayes 77% and 77.3% for Support Vector Machine. Outcomes show a significant accuracy of the methods." @default.
- W2970642414 created "2019-09-05" @default.
- W2970642414 creator A5044242809 @default.
- W2970642414 creator A5053460352 @default.
- W2970642414 date "2019-03-01" @default.
- W2970642414 modified "2023-10-18" @default.
- W2970642414 title "Diabetes Prediction Using Different Machine Learning Approaches" @default.
- W2970642414 cites W1603920668 @default.
- W2970642414 cites W2007281290 @default.
- W2970642414 cites W2443862987 @default.
- W2970642414 cites W2735762027 @default.
- W2970642414 cites W2783692386 @default.
- W2970642414 doi "https://doi.org/10.1109/iccmc.2019.8819841" @default.
- W2970642414 hasPublicationYear "2019" @default.
- W2970642414 type Work @default.
- W2970642414 sameAs 2970642414 @default.
- W2970642414 citedByCount "58" @default.
- W2970642414 countsByYear W29706424142020 @default.
- W2970642414 countsByYear W29706424142021 @default.
- W2970642414 countsByYear W29706424142022 @default.
- W2970642414 countsByYear W29706424142023 @default.
- W2970642414 crossrefType "proceedings-article" @default.
- W2970642414 hasAuthorship W2970642414A5044242809 @default.
- W2970642414 hasAuthorship W2970642414A5053460352 @default.
- W2970642414 hasConcept C105795698 @default.
- W2970642414 hasConcept C107673813 @default.
- W2970642414 hasConcept C119767625 @default.
- W2970642414 hasConcept C119857082 @default.
- W2970642414 hasConcept C12267149 @default.
- W2970642414 hasConcept C124101348 @default.
- W2970642414 hasConcept C134018914 @default.
- W2970642414 hasConcept C154945302 @default.
- W2970642414 hasConcept C169258074 @default.
- W2970642414 hasConcept C207201462 @default.
- W2970642414 hasConcept C2780598303 @default.
- W2970642414 hasConcept C2780929884 @default.
- W2970642414 hasConcept C33923547 @default.
- W2970642414 hasConcept C41008148 @default.
- W2970642414 hasConcept C52001869 @default.
- W2970642414 hasConcept C555293320 @default.
- W2970642414 hasConcept C71924100 @default.
- W2970642414 hasConcept C84525736 @default.
- W2970642414 hasConcept C94124525 @default.
- W2970642414 hasConceptScore W2970642414C105795698 @default.
- W2970642414 hasConceptScore W2970642414C107673813 @default.
- W2970642414 hasConceptScore W2970642414C119767625 @default.
- W2970642414 hasConceptScore W2970642414C119857082 @default.
- W2970642414 hasConceptScore W2970642414C12267149 @default.
- W2970642414 hasConceptScore W2970642414C124101348 @default.
- W2970642414 hasConceptScore W2970642414C134018914 @default.
- W2970642414 hasConceptScore W2970642414C154945302 @default.
- W2970642414 hasConceptScore W2970642414C169258074 @default.
- W2970642414 hasConceptScore W2970642414C207201462 @default.
- W2970642414 hasConceptScore W2970642414C2780598303 @default.
- W2970642414 hasConceptScore W2970642414C2780929884 @default.
- W2970642414 hasConceptScore W2970642414C33923547 @default.
- W2970642414 hasConceptScore W2970642414C41008148 @default.
- W2970642414 hasConceptScore W2970642414C52001869 @default.
- W2970642414 hasConceptScore W2970642414C555293320 @default.
- W2970642414 hasConceptScore W2970642414C71924100 @default.
- W2970642414 hasConceptScore W2970642414C84525736 @default.
- W2970642414 hasConceptScore W2970642414C94124525 @default.
- W2970642414 hasLocation W29706424141 @default.
- W2970642414 hasOpenAccess W2970642414 @default.
- W2970642414 hasPrimaryLocation W29706424141 @default.
- W2970642414 hasRelatedWork W2084779923 @default.
- W2970642414 hasRelatedWork W2970642414 @default.
- W2970642414 hasRelatedWork W2979979539 @default.
- W2970642414 hasRelatedWork W4205478082 @default.
- W2970642414 hasRelatedWork W4205958290 @default.
- W2970642414 hasRelatedWork W4210616724 @default.
- W2970642414 hasRelatedWork W4249746146 @default.
- W2970642414 hasRelatedWork W4280583453 @default.
- W2970642414 hasRelatedWork W4281846282 @default.
- W2970642414 hasRelatedWork W4283016678 @default.
- W2970642414 isParatext "false" @default.
- W2970642414 isRetracted "false" @default.
- W2970642414 magId "2970642414" @default.
- W2970642414 workType "article" @default.