Distributed Skin Lesion Analysis Across Decentralised Data Sources...Medical Informatics Europe, Public Health and Informatics Conference (Virtual), 29-31 May, 2021.
Skin cancer has become the most common cancer type. Research has applied image processing and analysis tools to support and improve the diagnose process. Conventional procedures usually centralise data from various data sources to a single location and execute the analysis tasks on central servers....
| Publicado en: | Studies in Health Technology & Informatics no. 281; pp. 352 - 357 |
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| Autores principales: | , , , , , , |
| Formato: | pictorial proceedings research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2021
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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=150593567&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 150593567 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09269630 U1V jtl: Studies in Health Technology & Informatics issn: 09269630 maglogo: N pubinfo: dt: 2021 iid: 281 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 150593567 150593567 150593567 10.3233/SHTI210179 150593567 ppf: 352 ppct: 5 formats: tig: atl: Distributed Skin Lesion Analysis Across Decentralised Data Sources...Medical Informatics Europe, Public Health and Informatics Conference (Virtual), 29-31 May, 2021. aug: au: MOU, Yongli WELTEN, Sascha JABERANSARY, Mehrshad UCER YEDIEL, Yeliz KIRSTEN, Toralf DECKER, Stefan BEYAN, Oya affil: RWTH Aachen University, Germany sug: subj: Skin Neoplasms Analysis Congresses and Conferences ab: Skin cancer has become the most common cancer type. Research has applied image processing and analysis tools to support and improve the diagnose process. Conventional procedures usually centralise data from various data sources to a single location and execute the analysis tasks on central servers. However, centralisation of medical data does not often comply with local data protection regulations due to its sensitive nature and the loss of sovereignty if data providers allow unlimited access to the data. The Personal Health Train (PHT) is a Distributed Analytics (DA) infrastructure bringing the algorithms to the data instead of vice versa. By following this paradigm shift, it proposes a solution for persistent privacy-related challenges. In this work, we present a feasibility study, which demonstrates the capability of the PHT to perform statistical analyses and Machine Learning on skin lesion data distributed among three Germany-wide data providers. pubtype: Academic Journal doctype: pictorial proceedings research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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