Algorithm-assisted diagnosis of Hirschsprung’s disease – evaluation of robustness and comparative image analysis on data from various labs and slide scanners
Abstract Background Differences in the preparation, staining and scanning of digital pathology slides create significant pre-analytic variability. Algorithm-assisted tools must be able to contend with this variability in order to be applicable in clinical practice. In a previous study, a decision su...
Main Authors: | Ariel Greenberg, Benzion Samueli, Shai Farkash, Yaniv Zohar, Shahar Ish-Shalom, Rami R. Hagege, Dov Hershkovitz |
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Format: | Article |
Language: | English |
Published: |
BMC
2024-02-01
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Series: | Diagnostic Pathology |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13000-024-01452-x |
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