New Promising Diagnostic Signatures in Histopathological Diagnosis
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".
Deadline for manuscript submissions: 31 July 2024 | Viewed by 390
Special Issue Editor
Special Issue Information
Dear Colleagues,
Histopathological diagnosis has been at the backbone of clinical medicine for over a century, as the microscopic examination of tissue samples can provide detailed insights into the nature, origin, and progression of diseases. Recent advancements in molecular biology, imaging techniques, and data analytics have led to the discovery of new diagnostic signatures. Some general areas where these new promising signatures have been emerging: artificial intelligence and machine learning, immunohistochemistry (IHC) markers, molecular diagnostics, digital pathology, liquid biopsies, quantitative histopathology, deep learning, and convolutional neural networks.
It's crucial to understand that while these advancements hold promise, they also come with challenges. The interpretation of complex data sets, integration of various diagnostic tools, and establishing robustness and reproducibility are all areas that need further work. The integration of various diagnostic signatures from multiple sources (like combining genomic data with histopathological images) will likely provide even more refined and accurate diagnostic tools for clinicians.
The purpose of this Special Issue is to explore the new frontiers in pathology as well as the integration of these new perspectives for the benefit of the patient.
Prof. Dr. Ovidiu Laurean Pop
Guest Editor
Manuscript Submission Information
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Keywords
- AI
- IHC
- digital pathology
- liquid biopsies
- deep learning
- neural network
