Digital pathology
- Submission status
- Open
- Submission deadline
Pathological examination of tissue has long been used in the diagnosis of disease. However, recent advances in imaging technologies have allowed for us to digitize pathology, which opens new avenues of exploration. Digital pathology not only increases our ability to analyze pathological slides computationally, including using machine learning, to provide diagnostic and theragnostic data, but it also allows for telepathology, increasing collaboration and improving diagnostic capabilities in low-resource areas where such tasks may have previously been unavailable. This digitization also allows us to gather additional data beyond traditional pathological staining, further improving our understanding of disease.
This Collection welcomes original research into digital pathology, including studies examining technologies for digitizing pathology and machine learning techniques for digitized data.
Editors
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Zeeshan Ahmed, PhD
Rutgers Health, USA
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Madhusudhanan Balasubramanian, PhD
The University of Memphis, USA
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Andrew J, PhD
Manipal Academy of Higher Education, India
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Sandeep Kumar Singhal, PhD
University of North Dakota, USA
Collections articles undergo Scientific Reports' standard peer review process and are subject to all of the journal’s standard policies. This includes the journal’s policy on competing interests. The Guest Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Guest Editors have competing interests is handled by another Editorial Board Member who has no competing interests. For more information, refer to our Collections guidelines.
This Collection has not been supported by sponsorship.
