Publication:
Applied Swarm-based medicine: collecting decision trees for patterns of algorithms analysis.

cris.virtualsource.author-orcidad339919-0d74-42e0-b3c3-1794174c18f1
cris.virtualsource.author-orcid3d566b43-d28b-487e-a181-2e15fc2e7024
cris.virtualsource.author-orcidf487cffb-f2bf-474f-b340-82ba0402fad7
cris.virtualsource.author-orcid68108203-15d6-4ee0-94c4-da3709d4b634
datacite.rightsopen.access
dc.contributor.authorPanje, Cédric M
dc.contributor.authorGlatzer, Markus
dc.contributor.authorvon Rappard, Joscha Stefan
dc.contributor.authorRothermundt, Christian
dc.contributor.authorHundsberger, Thomas
dc.contributor.authorZumstein, Valentin
dc.contributor.authorPlasswilm, Ludwig
dc.contributor.authorPutora, Paul Martin
dc.date.accessioned2024-11-24T08:45:52Z
dc.date.available2024-11-24T08:45:52Z
dc.date.issued2017-08-16
dc.description.abstractBACKGROUND The objective consensus methodology has recently been applied in consensus finding in several studies on medical decision-making among clinical experts or guidelines. The main advantages of this method are an automated analysis and comparison of treatment algorithms of the participating centers which can be performed anonymously. METHODS Based on the experience from completed consensus analyses, the main steps for the successful implementation of the objective consensus methodology were identified and discussed among the main investigators. RESULTS The following steps for the successful collection and conversion of decision trees were identified and defined in detail: problem definition, population selection, draft input collection, tree conversion, criteria adaptation, problem re-evaluation, results distribution and refinement, tree finalisation, and analysis. CONCLUSION This manuscript provides information on the main steps for successful collection of decision trees and summarizes important aspects at each point of the analysis.
dc.description.sponsorshipUniversitätsklinik für Nephrologie und Hypertonie
dc.description.sponsorshipKantonsspital St. Gallen
dc.identifier.doi10.7892/boris.111819
dc.identifier.pmid28814269
dc.identifier.publisherDOI10.1186/s12874-017-0400-y
dc.identifier.urihttps://boris-portal.unibe.ch/handle/20.500.12422/190392
dc.language.isoen
dc.publisherBioMed Central
dc.relation.ispartofBMC Medical research methodology
dc.relation.issn1471-2288
dc.relation.organizationDCD5A442BB17E17DE0405C82790C4DE2
dc.subjectCancer Consensus Consensus finding Decision tree Radiotherapy Swarm-based medicine
dc.subject.ddc600 - Technology::610 - Medicine & health
dc.titleApplied Swarm-based medicine: collecting decision trees for patterns of algorithms analysis.
dc.typearticle
dspace.entity.typePublication
dspace.file.typetext
oaire.citation.issue1
oaire.citation.startPage123
oaire.citation.volume17
oairecerif.author.affiliationKantonsspital St. Gallen
oairecerif.author.affiliationUniversitätsklinik für Nephrologie und Hypertonie
oairecerif.author.affiliationKantonsspital St. Gallen
oairecerif.author.affiliationKantonsspital St. Gallen
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unibe.date.licenseChanged2019-10-22 18:28:24
unibe.description.ispublishedpub
unibe.eprints.legacyId111819
unibe.journal.abbrevTitleBMC MED RES METHODOL
unibe.refereedtrue
unibe.subtype.articlejournal

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