Matches in SemOpenAlex for { <https://semopenalex.org/work/W4207042103> ?p ?o ?g. }
Showing items 1 to 75 of
75
with 100 items per page.
- W4207042103 endingPage "11" @default.
- W4207042103 startingPage "1" @default.
- W4207042103 abstract "The demand for blood transfusion is rising gradually. Therefore, volunteer blood donors are needed to save the lives of patients. There are lot of volunteer donors in every society. But, the main problem people face is finding such donors at the right time. To locate potential blood donors, we collected data from the Maizbhandari Shah Emdadia blood donors’ group, which consists of 700 active volunteer blood donors. This study aims to choose potential volunteer donors efficiently at the emergency time from the Maizbhandari Shah Emdadia blood donors’ group based on their past data. We have developed two models, namely descriptive and predictive models, using data mining techniques. The descriptive model analyzes data patterns and explores the donors’ behaviour. A data mining clustering algorithm was used to develop the descriptive model. The underlying factors of donors' intention to donate blood were identified and evaluated using this descriptive model. These factors were then utilized to develop the predictive model, which in turn assists to predict whether a donor will donate blood or not during an emergency. The findings of these two models will assist the clinical experts in locating potential volunteer blood donors within the shortest period and thus save valuable lives." @default.
- W4207042103 created "2022-01-26" @default.
- W4207042103 date "2021-08-28" @default.
- W4207042103 modified "2023-10-17" @default.
- W4207042103 title "DELVING INTO BLOOD TRANSFUSIONS DATA THROUGH DATA MINING: A STUDY OF MAIZBHANDARI SHAH EMDADIA BLOOD DONORS GROUP TO SELECT VOLUNTEER BLOOD DONORS EFFICIENTLY" @default.
- W4207042103 cites W2070855716 @default.
- W4207042103 cites W2133990480 @default.
- W4207042103 cites W2894674282 @default.
- W4207042103 cites W2905559315 @default.
- W4207042103 cites W2951032137 @default.
- W4207042103 cites W2954204776 @default.
- W4207042103 cites W2960755572 @default.
- W4207042103 cites W2972317233 @default.
- W4207042103 cites W3016284017 @default.
- W4207042103 cites W3021177294 @default.
- W4207042103 cites W3022563550 @default.
- W4207042103 cites W3046575914 @default.
- W4207042103 doi "https://doi.org/10.46281/aijmsr.v10i1.1308" @default.
- W4207042103 hasPublicationYear "2021" @default.
- W4207042103 type Work @default.
- W4207042103 citedByCount "0" @default.
- W4207042103 crossrefType "journal-article" @default.
- W4207042103 hasBestOaLocation W42070421031 @default.
- W4207042103 hasConcept C105795698 @default.
- W4207042103 hasConcept C142546437 @default.
- W4207042103 hasConcept C154945302 @default.
- W4207042103 hasConcept C17744445 @default.
- W4207042103 hasConcept C203014093 @default.
- W4207042103 hasConcept C2776768635 @default.
- W4207042103 hasConcept C2780014101 @default.
- W4207042103 hasConcept C2993617979 @default.
- W4207042103 hasConcept C3018377353 @default.
- W4207042103 hasConcept C33923547 @default.
- W4207042103 hasConcept C39549134 @default.
- W4207042103 hasConcept C39896193 @default.
- W4207042103 hasConcept C41008148 @default.
- W4207042103 hasConcept C6557445 @default.
- W4207042103 hasConcept C71924100 @default.
- W4207042103 hasConcept C73555534 @default.
- W4207042103 hasConcept C86803240 @default.
- W4207042103 hasConceptScore W4207042103C105795698 @default.
- W4207042103 hasConceptScore W4207042103C142546437 @default.
- W4207042103 hasConceptScore W4207042103C154945302 @default.
- W4207042103 hasConceptScore W4207042103C17744445 @default.
- W4207042103 hasConceptScore W4207042103C203014093 @default.
- W4207042103 hasConceptScore W4207042103C2776768635 @default.
- W4207042103 hasConceptScore W4207042103C2780014101 @default.
- W4207042103 hasConceptScore W4207042103C2993617979 @default.
- W4207042103 hasConceptScore W4207042103C3018377353 @default.
- W4207042103 hasConceptScore W4207042103C33923547 @default.
- W4207042103 hasConceptScore W4207042103C39549134 @default.
- W4207042103 hasConceptScore W4207042103C39896193 @default.
- W4207042103 hasConceptScore W4207042103C41008148 @default.
- W4207042103 hasConceptScore W4207042103C6557445 @default.
- W4207042103 hasConceptScore W4207042103C71924100 @default.
- W4207042103 hasConceptScore W4207042103C73555534 @default.
- W4207042103 hasConceptScore W4207042103C86803240 @default.
- W4207042103 hasLocation W42070421031 @default.
- W4207042103 hasOpenAccess W4207042103 @default.
- W4207042103 hasPrimaryLocation W42070421031 @default.
- W4207042103 hasRelatedWork W11619970 @default.
- W4207042103 hasRelatedWork W1270804 @default.
- W4207042103 hasRelatedWork W139576 @default.
- W4207042103 hasRelatedWork W14440009 @default.
- W4207042103 hasRelatedWork W17647556 @default.
- W4207042103 hasRelatedWork W2656838 @default.
- W4207042103 hasRelatedWork W4830101 @default.
- W4207042103 hasRelatedWork W8806344 @default.
- W4207042103 hasRelatedWork W9374611 @default.
- W4207042103 hasRelatedWork W16339674 @default.
- W4207042103 isParatext "false" @default.
- W4207042103 isRetracted "false" @default.
- W4207042103 workType "article" @default.