Digital Technologies to Improve Diagnostic Cytopathology: Future Outlook

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomedical Engineering and Biomaterials".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 77

Special Issue Editor


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Guest Editor
Facoltà di Medicina e Psicologia, Sede Ospedale S. Andrea Via di Grottarossa 1035, Università Sapienza, 00189 Roma, Italy
Interests: artificial intelligence; machine learning; neural network for cancer cells; diagnostic cytopathology

Special Issue Information

Dear Colleagues,

Advancements in technology and AI-driven tools are revolutionizing cytopathology. The ability to scan, store, view and share images, combined with machine learning applications, is expanding alongside the field itself, providing significant opportunities for professional growth. Digital technologies, such as virtual and augmented reality and natural language processing, could offer current and future generations new ways of working. A traditional microscope could be complemented by a 3D view of cytological samples, revealing critical morphological details; diagnostic uncertainties, such as in the decision to use a specific antibody in immunohistochemistry for differential diagnoses, could be overcome by virtual cytologists; similarly, the simultaneous visualization of the same cytological sample by other pathologists could facilitate collaborative case discussions. The integration of digital-driven diagnostic methodologies—including those involving AI—with traditional approaches will improve their effectiveness and patient care in the era of precision medicine. This Special Issue represents an opportunity for cytopathologists and those interested in the field to exchange ideas, laboratory experiences, and to potentially collaborate through articles and reviews on the possibility of developing new technologies that could improve cytopathological diagnostics.

Dr. Enrico Giarnieri
Guest Editor

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Keywords

  • machine learning
  • cytopathology
  • digital cytology
  • computer-aided diagnosis
  • virtual reality
  • natural language process

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This special issue is now open for submission.
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