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Since the early 2000s, computer-mediated communication (CMC) has grown rapidly, playing a crucial role in self-development. A key distinction between CMC and real-life interactions is the lack of a physically present partner. This absence makes non-verbal cues such as facial expressions, body language, and paralinguistic signals unavailable in CMC platforms like email, instant messaging, or social media. The lack of these cues can create ambiguity and complicate how feedback is interpreted.The...
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Digital pathology: semper ad meliora.

Simone L Van Es1

  • 1Department of Pathology, School of Medical Sciences, UNSW, Sydney, NSW, Australia.

Pathology
|December 8, 2018
PubMed
Summary

This review summarizes digital pathology advancements, covering its diagnostic performance, efficiency, and challenges. It explores digital pathology

Area of Science:

  • Medical Informatics
  • Pathology

Background:

  • Digital pathology offers a transformative approach to traditional histopathology and cytopathology.
  • Digitization presents unique challenges, particularly in cytopathology.

Purpose of the Study:

  • To provide an evidence-based review of digital pathology's evolution, current applications, and future potential.
  • To assess the diagnostic performance and user perceptions of digital pathology tools.

Main Methods:

  • Comprehensive literature review of digital pathology systems and applications.
  • Analysis of studies comparing digital and conventional pathology diagnostic accuracy and efficiency.

Main Results:

  • Digital pathology demonstrates comparable diagnostic performance to conventional methods.
Keywords:
WSIcytopathologydigital microscopydigital pathologyhistopathologywhole slide images

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  • Key considerations include time/cost efficiency, user learning curves, and system validation.
  • User perceptions and acceptance are crucial for successful implementation.
  • Conclusions:

    • Digital pathology is a viable diagnostic tool with significant potential for efficiency and data generation.
    • Addressing challenges in education, quality assurance, and system validation is essential for future adoption.
    • The integration of 'big data' from digital pathology will shape the future of the field.