Modern Pathology, Artificial Intelligence and Personalized Therapy in Gastrointestinal Cancer
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Therapy".
Deadline for manuscript submissions: 31 March 2026 | Viewed by 1617
Special Issue Editor
Special Issue Information
Dear Colleagues,
Gastrointestinal (GI) cancers occur with high prevalence and mortality in the United States and worldwide. Early diagnosis and optimized therapy remain major challenges in the treatment of GI cancer. Personalized cancer therapy is a new approach that involves tailoring prevention and treatment recommendations to the individual patient based on their genetic/genomic characteristics and tumor-related biomarkers. Its evolution has instigated a new era in the fight against cancer.
Advancements in technology and molecular diagnostics have increased our understanding and interpretation of the genomic and proteomic properties of cancers, and revealed many specific biomarkers that are now being incorporated into diagnostic and treatment decision-making algorithms. Molecular pathology is rapidly becoming a cornerstone of personalized therapy for cancers, including GI cancers.
Digital pathology initiated the shift from traditional histopathology using microscopy to virtual images on the computer, and has promoted the use of artificial intelligence (AI) and machine learning (ML) by pathologists in clinical practice. AI in pathology comprises computational search algorithms, machine learning, and deep learning models. AI has been used to identify novel diagnostic and prognostic biomarker signatures on tissue images of various types of cancer, and has also been used to create more quantitative, detailed, objective, and reproducible assessments of these tissue biomarkers.
This Special Issue of Cancers aims to introduce the latest original studies and reviews on molecular biomarkers, digital pathology, and personalized therapy in GI cancers.
Dr. Wenqing Cao
Guest Editor
Manuscript Submission Information
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Keywords
- molecular pathology
- biomarkers
- digital pathology
- targeted therapy
- gastric cancer
- colon
- liver
- pancreas
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