Flex Conference (Physical / Digital)

International Conference on Computational Pathology and Applications - (ICOCPA-27)

4th - 5th June 2027 , Riga - Latvia

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Call For Papers

The (ICOCPA-27) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Pathology, Computational Science are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Computational Tools for Pathology Applications
  • Machine Learning in Pathological Analysis
  • Digital Pathology and Its Applications
  • Data Integration in Computational Pathology
  • AI-Driven Diagnostics in Pathology
  • Pathology Image Analysis Techniques
  • Bioinformatics in Pathological Research
  • Telepathology Applications in Remote Diagnosis
  • Ethics of Computational Pathology Practices
  • Innovative Software Solutions for Pathology
  • Interdisciplinary Approaches in Computational Pathology
  • Future of Digital Pathology Technologies
  • Clinical Applications of Computational Pathology
  • Pathology Data Visualization Techniques
  • Impact of Big Data on Pathology
  • Computational Pathology in Personalized Medicine
  • Emerging Trends in Pathology Informatics
  • Collaboration Between Pathologists and Engineers
  • Regulatory Considerations in Computational Pathology
  • Education in Computational Pathology Techniques

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.