Clinical user interfaces that learn from experience.
Clinical data entry is one key to success in health information systems that is not a matter of technology alone, but of appropriateness and usability of design. We review the technology of adaptive user interfaces and learning agents. In these technologies we see the potential to improve the usabil...
| Publicado en: | Informatics in Primary Care Vol. 10; no. 4; pp. 217 - 221 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Radcliffe Publishing
2002
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=106698883&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 106698883 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14760320 NAN jtl: Informatics in Primary Care issn: 14760320 maglogo: N pubinfo: dt: 2002 vid: 10 iid: 4 pid: 13723 pub: Radcliffe Publishing artinfo: ui: 106698883 2004030323 106698883 ppf: 217 ppct: 4 formats: tig: atl: Clinical user interfaces that learn from experience. aug: au: Gadzhanova S Stanek J Warren J affil: University of South Australia, School of Computer & Information Sciences, Advanced Computing Research Centre, Mawson Lakes Campus, Mawson Lakes SA 5095; jan.stanek@unisa.edu.au sug: subj: User-Computer Interface Data Management Family Practice Expert Systems Knowbots ab: Clinical data entry is one key to success in health information systems that is not a matter of technology alone, but of appropriateness and usability of design. We review the technology of adaptive user interfaces and learning agents. In these technologies we see the potential to improve the usability of general practice clinical workstations through machine-learnt adaptation to the user, the patient and the specific situation. Use of intelligent split menus that adapt based on past clinical encounters is one specific adaptive interface method that has shown potential by simulation. We are undertaking research in 'expert in the loop' use of data mining for iterative refinement of clinical workstation adaptation with an eye to significantly improving general practice data entry quality. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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