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Swiss digital pathology recommendations: results from a Delphi process conducted by the Swiss Digital Pathology Consortium of the Swiss Society of Pathology.

Andrew JanowczykInti ZlobecCedric WalkerSabina A BerezowskaViola HuschauerMarianne TinguelyJoel KupferschmidThomas MalletDoron MerklerMario KreutzfeldtRadivoje GasicTilman T RauLuca MazzucchelliIsgard EybergGieri CathomasKirsten D MertzViktor Hendrik KoelzerDavide SoldiniWolfram JochumMatthias RössleMaurice HenkelRainer Grobholznull null
Published in: Virchows Archiv : an international journal of pathology (2023)
Integration of digital pathology (DP) into clinical diagnostic workflows is increasingly receiving attention as new hardware and software become available. To facilitate the adoption of DP, the Swiss Digital Pathology Consortium (SDiPath) organized a Delphi process to produce a series of recommendations for DP integration within Swiss clinical environments. This process saw the creation of 4 working groups, focusing on the various components of a DP system (1) scanners, quality assurance and validation of scans, (2) integration of Whole Slide Image (WSI)-scanners and DP systems into the Pathology Laboratory Information System, (3) digital workflow-compliance with general quality guidelines, and (4) image analysis (IA)/artificial intelligence (AI), with topic experts for each recruited for discussion and statement generation. The work product of the Delphi process is 83 consensus statements presented here, forming the basis for "SDiPath Recommendations for Digital Pathology". They represent an up-to-date resource for national and international hospitals, researchers, device manufacturers, algorithm developers, and all supporting fields, with the intent of providing expectations and best practices to help ensure safe and efficient DP usage.
Keyphrases
  • artificial intelligence
  • deep learning
  • machine learning
  • clinical practice
  • healthcare
  • big data
  • primary care
  • computed tomography
  • magnetic resonance imaging
  • electronic health record
  • social media