Designing a Digital Health Solution: A Platform for Automated Surveillance of Fungal Infection...19th World Congress on Medical and Health Informatics, July 8-12, 2023, New South Wales, Australia
Surveillance of invasive fungal infection (IFI) requires laborious review of multiple sources of clinical information, while applying complex criteria to effectively identify relevant infections. These processes can be automated using artificial intelligence (AI) methodologies, including applying na...
| Publicado en: | Studies in Health Technology & Informatics Vol. 310; pp. 1454 - 1456 |
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| Autores principales: | , , , , |
| Formato: | pictorial proceedings research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2023
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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=175249050&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 175249050 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09269630 U1V jtl: Studies in Health Technology & Informatics issn: 09269630 maglogo: N pubinfo: dt: 2023 vid: 310 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 175249050 175249050 175249050 10.3233/SHTI231241 175249050 ppf: 1454 ppct: 2 formats: tig: atl: Designing a Digital Health Solution: A Platform for Automated Surveillance of Fungal Infection...19th World Congress on Medical and Health Informatics, July 8-12, 2023, New South Wales, Australia aug: au: KHANINA, Anna ROZOVA, Vlada ELKINS, Sri VERSPOOR, Karin THURSKY, Karin affil: National Centre for Infections in Cancer, Peter MacCallum Cancer Centre, Melbourne, Australia sug: subj: Digital Health Mycoses Artificial Intelligence Utilization Automation Methods Disease Surveillance Methods Congresses and Conferences New South Wales New South Wales Human Natural Language Processing User-Computer Interface Conceptual Framework Problem Solving ab: Surveillance of invasive fungal infection (IFI) requires laborious review of multiple sources of clinical information, while applying complex criteria to effectively identify relevant infections. These processes can be automated using artificial intelligence (AI) methodologies, including applying natural language processing (NLP) to clinical reports. However, developing a practically useful automated IFI surveillance tool requires consideration of the implementation context. We employed the Design Thinking Framework (DTF) to focus on the needs of end users of the tool to ensure sustained user engagement and enable its prospective validation. DTF allowed iterative generation of ideas and refinement of the final digital health solution. We believe this approach is key to increasing the likelihood that the solution will be implemented in clinical practice. pubtype: Academic Journal doctype: pictorial proceedings research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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