Digital Pathology 2.0
A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Molecular Medicine".
Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 4008
Special Issue Editor
Interests: cancer biomarker; evidence-based medicine; extracellular vesicles; genomics; microRNA; molecular diagnostics; non-coding RNAs; nasopharyngeal carcinoma; next-generation sequencing; non-small cell lung cancer; proteomics; drug repurposing and bioinformatics
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Special Issue Information
Dear Colleagues,
The invention of the microscope was a milestone for modern medicine and for mankind. Nowadays, disease diagnosis heavily relies on definitive decisions from histopathological analysis of the specimen. In the current era, digital pathology is a dynamic, image-based environment that incorporates the acquisition, management, and interpretation of pathology information generated from a digitized glass slide. Digital slides are created when glass slides are captured by a scanning device, and they provide a high-resolution digital image that can be viewed on a computer screen or mobile device.
Digital pathology can improve the quality of diagnosis in meaningful ways, including reduced errors, improved analysis, and better views. Thus, digital pathology enhances productivity because of the improved workflow, reduced turnaround times, and more innovative design. However, it is also challenging current conventional settings, and the integration of digital pathology should be well planned out.
This Special Issue serves as a platform to propel the field of digital pathology.
The scope of this Special Issue includes, but is not limited to, the following:
- Virtual multiplex immunohistochemistry;
- Automated classification of whole-slide images based on deep learning;
- Super-resolution recurrent convolutional neural networks;
- Challenges in analysis of digital tissue biopsies;
- Translational artificial intelligence and deep learning in diagnostic pathology;
- Efficient algorithms for digital image analysis;
- Computational pathology, best practices, and recommendations;
- Sensitivity analysis in digital pathology;
- Artificial intelligence algorithms in digital pathology;
- Automated tumor recognition and scoring for biomarkers.
Dr. William Cho
Guest Editor
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