Attitudes of nursing staff towards electronic patient records A questionnaire survey.docx
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Attitudes of nursing staff towards electronic patient records A questionnaire survey.docx
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AttitudesofnursingstafftowardselectronicpatientrecordsAquestionnairesurvey
Animagecontrastenhancementmethodbasedongeneticalgorithm
PatternRecognitionLetters
Contrastenhancementplaysafundamentalroleinimage/videoprocessing.HistogramEqualization(HE)isoneofthemostcommonlyusedmethodsforimagecontrastenhancement.However,HEandmostothercontrastenhancementmethodsmayproduceun-naturallookingimagesandtheimagesobtainedbythesemethodsarenotdesirableinapplicationssuchasconsumerelectronicproductswherebrightnesspreservationisnecessarytoavoidannoyingartifacts.Tosolvesuchproblems,weproposedanefficientcontrastenhancementmethodbasedongeneticalgorithminthispaper.Theproposedmethodusesasimpleandnovelchromosomerepresentationtogetherwithcorrespondingoperators.Experimentalresultsshowedthatthismethodmakesnaturallookingimagesespeciallywhenthedynamicrangeofinputimageishigh.Also,ithasbeenshownbysimulationresultsthattheproposedgeneticmethodhadbetterresultsthanrelatedonesintermsofcontrastanddetailenhancementandtheresultedimagesweresuitableforconsumerelectronicproducts.
ArticleOutline
1.Introduction
2.Proposedgeneticmethod
2.1.Chromosomestructure
2.2.Fitnessfunction
2.3.Selectionalgorithm
2.4.Crossoverandmutationoperators
2.5.Terminatingcriteria
3.Experimentalresults
4.Conclusion
References
Candesignprinciplesoftraditionallearningtheoriesbefulfilledbycomputer-basedtrainingsystemsinmedicine:
TheexampleofCAMPUS OriginalResearchArticle
InternationalJournalofMedicalInformatics
Purpose
Computer-basedtraining(CBT)systemsofferthepotentialtoefficientlysupportmodernteachingandlearning.However,itisstillunknownifasimilarefficientlearningexperiencebuiltonsoundlearningtheoriesandcorrespondingdesignprinciplescanbecreatedinthecomplexhealthcareenvironment.Thepurposeofthispaperistoanalysetowhatextentlearningtheoriesandcorrespondingdesignprinciplesarerelevantandcansuccessfullybeappliedincomputer-basedtraininginmedicine.
Methods
Weusethecase-basedCBTsystemCAMPUSasanexampleforaCBTsystemcurrentlyusedtoenhancethemedicalteachingandlearningexperience.Weapplytwowell-acceptedlearningtheories(Bloom'staxonomyandpracticefields)andrelateddesignprinciplestodeterminetowhatextenttheyarerelevantandfulfilledinthecontextofCAMPUS.
Results
Wedemonstratethatinprincipletheselearningtheoriesanddesignprinciplescanbeimplementedusingcomputer-basedtraining.However,notalldesignprinciplescanbefulfilledbythesystemalone;rathertheintegrationofthesystemintoadequate–traditionalorvirtual–teachingandlearningenvironmentsisessential.
Conclusions
TraditionallearningtheoriesanddesignprinciplesareavaluablemeansindesigningadequateCBTsystemsinmedicine.TheycanbesuccessfullyimplementedinCBTsystemsformedicaleducationifthesystemitselfisadequatelyintegratedintoteachingandlearningenvironments.
ArticleOutline
1.Introduction
2.Methods
2.1.CAMPUS
2.2.Bloom'staxonomy
2.3.Practicefields
3.Results
3.1.CAMPUSandBloom'staxonomy
3.2.CAMPUSandpracticefields
4.Discussion
5.Conclusion
References
Listeningtothevoicesofpatientswithcancer,theiradvocatesandtheirnurses:
Ahermeneutic-phenomenologicalstudyofqualitynursingcare OriginalResearchArticle
EuropeanJournalofOncologyNursing
Thisarticlepresentsthefindingsfromahermeneutic-phenomenologicalstudylookingatthemeaningsof“qualitynursingcare”throughtheexperiencesofpatientswithcancer,theiradvocatesandtheirnurses.Twenty-fivepatientswereinterviewedfromwhichfifteenalsoparticipatedintwofocusgroups.Sixpatients'advocatesparticipatedinafocusgroupandtwentynurseswereindividuallyinterviewed.TheinformantscamefromthethreemajorhospitalsinCypruswhichprovidein-patientcancercare.Patients'advocatescamefromthetwomajorcancerassociationsinCyprus.Havinganalysedthedata,sevenmajorthemeswereidentified:
receivingcareineasilyaccessiblecancercareservices,beingcaredforbynurseswhoeffectivelycommunicatewiththemandtheirfamiliesandprovideemotionalsupport,beingempoweredbynursesthroughinformationgiving,beingcaredforbyclinicallycompetentnurses,nursesaddressingtheirreligiousandspiritualneeds,beingcaredforinanursingenvironmentwhichpromotesshareddecision-making,andpatientsbeingwithandinvolvingthefamilyinthecare.Thesefindingsstresstheneedtointegratetheseaspectsinthecareofpatientswithcancer.Indoingso,nurseswillneedsupportandadequatetraininginordertoacquiretherelevantskillstowardsbettercaringforthepatients.
ArticleOutline
Introduction
Aimofthestudy
Methods
Studydesign,samplesandsettings
Thehermeneutic-phenomenologicalmethod
Ethicalpermission
Datacollection
Dataanalysis
Findingsanddiscussion
Beingtreatedforcancerineasilyaccessibleservices
Beingcaredforbynurseswhoprovideemotionalsupportandeffectivelycommunicatingwiththemandtheirfamilies
Beinggivenhealth-relatedinformationbynurses
Beingcaredforbynurseswithclinicalcompetencies
Havingtheirreligiousandspiritualneedsmetbythenurse
Beingcaredforbynurseswhopromoteshareddecision-making
Promotingfamilypresenceandinvolvementinthecare
Methodologicalreflections
Implicationsfornursingpracticeandcontributiontoknowledge
Conflictofintereststatement
References
GA-basedmethodforfeatureselectionandparametersoptimizationformachinelearningregressionappliedtosoftwareeffortestimation OriginalResearchArticle
InformationandSoftwareTechnology
Insoftwareindustry,projectmanagersusuallyrelyontheirpreviousexperiencetoestimatethenumbermen/hoursrequiredforeachsoftwareproject.Theaccuracyofsuchestimatesisakeyfactorfortheefficientapplicationofhumanresources.Machinelearningtechniquessuchasradialbasisfunction(RBF)neuralnetworks,multi-layerperceptron(MLP)neuralnetworks,supportvectorregression(SVR),baggingpredictorsandregression-basedtreeshaverecentlybeenappliedforestimatingsoftwaredevelopmenteffort.Someworkshavedemonstratedthatthelevelofaccuracyinsoftwareeffortestimatesstronglydependsonthevaluesoftheparametersofthesemethods.Inaddition,ithasbeenshownthattheselectionoftheinputfeaturesmayalsohaveanimportantinfluenceonestimationaccuracy.
Objective
Thispaperproposesandinvestigatestheuseofageneticalgorithmmethodforsimultaneously
(1)selectanoptimalinputfeaturesubsetand
(2)optimizetheparametersofmachinelearningmethods,aimingatahigheraccuracylevelforthesoftwareeffortestimates.
Method
Simulationsarecarriedoutusingsixbenchmarkdatasetsofsoftwareprojects,namely,Desharnais,NASA,COCOMO,Albrecht,KemererandKotenandGray.Theresultsarecomparedtothoseobtainedbymethodsproposedintheliteratureusingneuralnetworks,supportvectormachines,multipleadditiveregressiontrees,bagging,andBayesianstatisticalmodels.
Results
Inalldatasets,thesimulationshaveshownthattheproposedGA-basedmethodwasabletoimprovetheperformanceofthemachinelearningmethods.Thesimulationshavealsodemonstratedthattheproposedmethodoutperformssomerecentmethodsreportedintherecentliteratureforsoftwareeffortestimation.Furthermore,theuseofGAforfeatureselectionconsiderablyreducedthenumberofinputfeaturesforfiveofthedatasetsusedinouranalysis.
Conclusions
Thecombinationofinputfeaturesselectionandparametersoptimizationofmachinelearningmethodsimprovestheaccuracyofsoftwaredevelopmenteffort.Inaddition,thisreducesmodelcomplexity,whichmayhelpunderstandingtherelevanceofeachinputfeature.Therefore,someinputparameterscanbeignoredwithoutlossofaccuracyintheestimations.
ArticleOutline
1.Introduction
2.Regressionmethods
2.1.Supportvectorregression
2.2.Multi-layerperceptron
2.3.Modeltrees
3.Geneticalgorithm
3.1.Geneticoperators
4.GA-basedfeatureselectionandparametersoptimization
4.1.Chromosomedesign
4.2.Fitnessfunction
4.3.SystemarchitecturefortheproposedGA-basedapproach
5.Experiments
5.1.Performancemetrics
5.2.Desharnaisdataset
5.3.NASAdataset
5.4.COCOMOdataset
5.5.Albrechtdataset
5.6.Kemererdataset
5.7.KotenandGraydataset
6.Conclusion
Towardsintegrationofclinicaldecisionsupportincommercialhospitalinformationsystemsusingdistributed,reusablesoftwareandknowledgecomponents OriginalResearchArticle
InternationalJournalofMedicalInformatics
Problem:
Clinicians'acceptanceofclinicaldecisionsupportdependsonitsworkflow-oriented,context-sensitiveaccessibilityandavailabilityatthepointofcare,integratedintotheElectronicPatientRecord(EPR).CommerciallyavailableHospitalInformationSystems(HIS)oftenfocusonadministrativetasksandmostlydonotprovideadditionalknowledgebasedfunctionality.Theirtraditionallymonolithicandclosedsoftwarearchitectureencumbersintegrationofandinteractionwithexternalsoftwaremodules.Ouraimwastodevelopmethodsandinterfacestointegrateknowledgesourcesintotwodifferentcommercialhospitalinformationsystemstoprovidethebestdecisionsupportpossiblewithinthecontextofavailablepatientdata.Methods:
Anexisting,provenstandalonescoringsystemforacuteabdominalpainwassupplementedbyacommunicationinterface.InbothHISwedefineddataentryforms
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