Matches in SemOpenAlex for { <https://semopenalex.org/work/W4229818893> ?p ?o ?g. }
Showing items 1 to 58 of
58
with 100 items per page.
- W4229818893 endingPage "1119" @default.
- W4229818893 startingPage "1115" @default.
- W4229818893 abstract "Nowadays in medical field the major concern lies in the field of liver, renal diseases. Liver is the largest organ in the body and it is the factory which processes all the foods we taken. We should keep liver in perfect condition. But today there were lot of Liver, renal damages occurred commonly. where sluggish lifestyle of humans and escalated alcohol abuse has become dangerously common, liver ,kidney health have regained focus. This can cause liver cirrhosis and liver dysfunction. The main solution for this is transplantation surgeries. In most of the cases, transplantation surgeries are successful. But after few days normal patients become die. its a very common news. This is because of the lack of ideal drug dosage prediction. Today all of the medical practitioners calculate manually using some patients responses towards the drug. So it is not a systematic approach. Only purely mathematical approach is available for calculating drug dosage. To achieve an optimal drug dosage calculation, proposed model will automate this system based on some patients response data like cell viability, drug trough level, Creatine Test result, biopsy result, MELD score etc using some artificial intelligence techniques like neural networks. The human and monetary of both optimal and Sub- optimal drug dosage may be deduced from the action of various optimized neural networks. Neural networks provide sceptical help to doctors. Currently there is no system will automize this dosage calculation. This calculation based on patients responses after transplantation surgery. Normally start with zero level dosage of medicines. After few days the ideal drug usage calculations occurred based on some observing patients different levels of data. Automate this system will help to doctors to calculate automatically the optimal usage of drugs makes precise calculations in the patients health." @default.
- W4229818893 created "2022-05-11" @default.
- W4229818893 date "2019-12-30" @default.
- W4229818893 modified "2023-10-01" @default.
- W4229818893 title "Automating the Drug Dosage of Tacrolimus for Liver, Renal Transplant Patients using Neural Network" @default.
- W4229818893 doi "https://doi.org/10.35940/ijitee.b1110.1292s219" @default.
- W4229818893 hasPublicationYear "2019" @default.
- W4229818893 type Work @default.
- W4229818893 citedByCount "1" @default.
- W4229818893 countsByYear W42298188932022 @default.
- W4229818893 crossrefType "journal-article" @default.
- W4229818893 hasBestOaLocation W42298188931 @default.
- W4229818893 hasConcept C119857082 @default.
- W4229818893 hasConcept C126322002 @default.
- W4229818893 hasConcept C141071460 @default.
- W4229818893 hasConcept C177713679 @default.
- W4229818893 hasConcept C2777214474 @default.
- W4229818893 hasConcept C2779609443 @default.
- W4229818893 hasConcept C2780035454 @default.
- W4229818893 hasConcept C2909675724 @default.
- W4229818893 hasConcept C2911091166 @default.
- W4229818893 hasConcept C41008148 @default.
- W4229818893 hasConcept C50644808 @default.
- W4229818893 hasConcept C71924100 @default.
- W4229818893 hasConcept C98274493 @default.
- W4229818893 hasConceptScore W4229818893C119857082 @default.
- W4229818893 hasConceptScore W4229818893C126322002 @default.
- W4229818893 hasConceptScore W4229818893C141071460 @default.
- W4229818893 hasConceptScore W4229818893C177713679 @default.
- W4229818893 hasConceptScore W4229818893C2777214474 @default.
- W4229818893 hasConceptScore W4229818893C2779609443 @default.
- W4229818893 hasConceptScore W4229818893C2780035454 @default.
- W4229818893 hasConceptScore W4229818893C2909675724 @default.
- W4229818893 hasConceptScore W4229818893C2911091166 @default.
- W4229818893 hasConceptScore W4229818893C41008148 @default.
- W4229818893 hasConceptScore W4229818893C50644808 @default.
- W4229818893 hasConceptScore W4229818893C71924100 @default.
- W4229818893 hasConceptScore W4229818893C98274493 @default.
- W4229818893 hasIssue "2S2" @default.
- W4229818893 hasLocation W42298188931 @default.
- W4229818893 hasOpenAccess W4229818893 @default.
- W4229818893 hasPrimaryLocation W42298188931 @default.
- W4229818893 hasRelatedWork W1973972854 @default.
- W4229818893 hasRelatedWork W2011017885 @default.
- W4229818893 hasRelatedWork W2385697996 @default.
- W4229818893 hasRelatedWork W2386960718 @default.
- W4229818893 hasRelatedWork W2418205605 @default.
- W4229818893 hasRelatedWork W2439875401 @default.
- W4229818893 hasRelatedWork W2475187906 @default.
- W4229818893 hasRelatedWork W2809601010 @default.
- W4229818893 hasRelatedWork W48730955 @default.
- W4229818893 hasRelatedWork W2525756941 @default.
- W4229818893 hasVolume "9" @default.
- W4229818893 isParatext "false" @default.
- W4229818893 isRetracted "false" @default.
- W4229818893 workType "article" @default.