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Digital Analysis of Immunostaining of ZW10 Interacting Protein in Human Lung Tissues

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Published on: May 1, 2019

Digital pathology world tour.

Paola Chiara Rizzo¹, Alessandro Caputo², Eddy Maddalena³

¹Department of Pathology and Diagnostics and Public Health, Section of Pathology, University Hospital of Verona, Verona, Italy.

|September 1, 2023

Summary

This summary is machine-generated.

Digital pathology (DP) shows rapid growth, but its use in routine clinical diagnostics remains limited. Analysis of scientific literature reveals most DP applications are non-diagnostic.

Keywords:

Artificial intelligence digital pathology image analysis systematic review whole slide imaging

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Area of Science:

Pathology
Medical Informatics

Background:

Digital pathology (DP) has a long history but is currently gaining significant attention.
Despite technological advancements, widespread adoption of DP for routine clinical diagnostics is slow.

Purpose of the Study:

To analyze the global adoption of digital pathology by examining published scientific literature.
To provide temporal and geographical insights into DP research and application trends.

Main Methods:

A systematic literature search was performed in PubMed-MEDLINE and Embase.
Inclusion criteria encompassed all published studies involving any application of digital pathology.

Main Results:

Out of 4888 retrieved articles, 4041 were included in the analysis.
Only 4% (147/4041) of studies utilized DP for routine diagnostic workflows.
The vast majority (96%) of DP applications were non-diagnostic, including artificial intelligence (33%), education (5%), reviews (17%), and technical research (45%).

Conclusions:

The study highlights a significant gap between the technological progress in DP and its integration into routine clinical practice.
The majority of published research focuses on non-diagnostic applications, indicating a need to accelerate the translation of DP into clinical diagnostics.