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Value of Public Cha...
Value of Public Challenges for the Development of Pathology Deep Learning Algorithms
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- Hartman, Douglas Joseph (author)
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
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- van der Laak, Jeroen, 1967- (author)
- Linköpings universitet,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands
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- Gurcan, Metin N (author)
- Center for Biomedical Informatics, Wake Forest School of Medicine, Winston Salem, NC, USA
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- Pantanowitz, Liron (author)
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
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(creator_code:org_t)
- Medknow Publications, 2020
- 2020
- English.
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In: Journal of Pathology Informatics. - : Medknow Publications. - 2229-5089 .- 2153-3539. ; 11
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https://liu.diva-por... (primary) (Raw object)
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https://doi.org/10.4...
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Abstract
Subject headings
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- The introduction of digital pathology is changing the practice of diagnostic anatomic pathology. Digital pathology offers numerous advantages over using a physical slide on a physical microscope, including more discriminative tools to render a more precise diagnostic report. The development of these tools is being facilitated by public challenges related to specific diagnostic tasks within anatomic pathology. To date, 24 public challenges related to pathology tasks have been published. This article discusses these public challenges and briefly reviews the underlying characteristics of public challenges and why they are helpful to the development of digital tools.
Subject headings
- SAMHÄLLSVETENSKAP -- Medie- och kommunikationsvetenskap -- Systemvetenskap, informationssystem och informatik med samhällsvetenskaplig inriktning (hsv//swe)
- SOCIAL SCIENCES -- Media and Communications -- Information Systems, Social aspects (hsv//eng)
Keyword
- Algorithm development; artificial intelligence; digital pathology algorithms; public challenges
Publication and Content Type
- ref (subject category)
- art (subject category)
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