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Joint Imaging Platform for Federated Clinical Data Analytics.

Jonas SchererMarco NoldenJens KleesiekJasmin MetzgerKlaus KadesVerena SchneiderMichael BachOliver SedlaczekAndreas Michael BucherThomas J VoglFrank GrünwaldJens-Peter KühnRalf-Thorsten HoffmannJörg KotzerkeOliver BethgeLars SchimmöllerGerald AntochHans-Wilhelm MüllerAndreas DaulKonstantin NikolaouChristian Peter la FougèreWolfgang G KunzMichael IngrishBalthasar Maria SchachtnerJens RickePeter BartensteinFelix NensaAlexander RadbruchLale UmutluMichael ForstingRobert SeifertKen HerrmannPhilipp MayerHans-Ulrich KauczorTobias PenzkoferBernd HammWinfried BrennerRoman KlöcknerChristoph DüberMathias SchreckenbergerRickmer BrarenGeorgios A KaissisMarcus MakowskiMatthias EiberAndrei GafitaRupert TragerWolfgang A WeberJakob NeubauerMarco ReisertMichael BockFabian BambergJuergen HennigPhilipp Tobias MeyerJuri RufUwe HaberkornStefan O SchoenbergTristan Anselm KuderPeter F NeherRalf O FlocaHeinz-Peter SchlemmerKlaus H Maier-Hein
Published in: JCO clinical cancer informatics (2021)
The results demonstrate the feasibility of using the JIP as a federated data analytics platform in heterogeneous clinical information technology and software landscapes, solving an important bottleneck for the application of AI to large-scale clinical imaging data.
Keyphrases
  • big data
  • electronic health record
  • high resolution
  • artificial intelligence
  • high throughput
  • data analysis
  • single cell