ReviewCancers2024
Digital Pathology for Better Clinical Practice.
Review in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed.
- Digital Pathology and the AI-Based Quantification of the Tumor Microenvironment in Gastrointestinal Cancer: From Tumor Budding and Tumor-Infiltrating Lymphocytes to Tertiary Lymphoid Structures.International journal of molecular sciences · 2026Review
- The critical role of accurate neoplastic cell percentage (NCP) assessment: investigating targeted training strategies for pulmonary biopsy and cytology specimens.Virchows Archiv : an international journal of pathology · 2026Article
- A Hybrid Lung and Colon Histopathological Image Classification Framework Using MobileNetV3-Small Deep Features and Differential Evolution Optimization.Diagnostics (Basel, Switzerland) · 2026Article
- Quantitative digital pathology reveals morphological and molecular correlates of tumor aggressiveness in prostate cancer.International urology and nephrology · 2026Article
- Intimal CD31-positive relative surfaces are associated with the dysfunction of autologous arteriovenous fistulas in patients receiving dialysis.International urology and nephrology · 2026Article
- Trends in the China pathologist workforce From 2010 to 2022.Frontiers in health services · 2026Article
- Comparison of digital displays for efficient diagnosis and accuracy.Journal of pathology informatics · 2026Article
- Perineural invasion in solid tumors: biological foundations and the emerging integration of machine learning and artificial intelligence.Frontiers in oncology · 2026Review
- Piezo1 ion channel: a core target for mechanotransduction in orthodontic alveolar bone remodeling.Frontiers in cell and developmental biology · 2026Review
- A Lightweight Cross-Gated Dual-Branch Attention Network for Colon and Lung Cancer Diagnosis from Histopathological Images.Medical sciences (Basel, Switzerland) · 2025Article
- Deep learning in bone marrow cytomorphology: advances in segmentation, classification, and clinical translation.Medical oncology (Northwood, London, England) · 2025Review
- Immunoprofiling at an Institutional Scale Reveals That High Numbers of Intratumoral CD8JCO precision oncology · 2025Article
- Immunoscore: redefining the landscape of colorectal cancer control and care.Future oncology (London, England) · 2025Review
- Systematic review and meta-analysis of deep learning for MSI-H in colorectal cancer whole slide images.NPJ digital medicine · 2025Article
- An equivalency and efficiency study for one year digital pathology for clinical routine diagnostics in an accredited tertiary academic center.Virchows Archiv : an international journal of pathology · 2025Review
- Double-Multiplex Immunostainings for Immune Profiling of Invasive Breast Carcinoma: Emerging Novel Immune-Based Biomarkers.International journal of molecular sciences · 2025Review
- Spatial‒temporal heterogeneities of liver cancer and the discovery of the invasive zone.Clinical and translational medicine · 2025Review
- A Narrative Review on the Role of Artificial Intelligence (AI) in Colorectal Cancer Management.Cureus · 2025Review
- Non-diagnostic time in digital pathology: An empirical study over 10 years.Journal of pathology informatics · 2024Article
- Models for the marrow: A comprehensive review of AI-based cell classification methods and malignancy detection in bone marrow aspirate smears.HemaSphere · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
(1) Background: Digital pathology (DP) is transforming the landscape of clinical practice, offering a revolutionary approach to traditional pathology analysis and diagnosis. (2) Methods: This innovative technology involves the digitization of traditional glass slides which enables pathologists to access, analyze, and share high-resolution whole-slide images (WSI) of tissue specimens in a digital format. By integrating cutting-edge imaging technology with advanced software, DP promises to enhance clinical practice in numerous ways. DP not only improves quality assurance and standardization but also allows remote collaboration among experts for a more accurate diagnosis. Artificial intelligence (AI) in pathology significantly improves cancer diagnosis, classification, and prognosis by automating various tasks. It also enhances the spatial analysis of tumor microenvironment (TME) and enables the discovery of new biomarkers, advancing their translation for therapeutic applications. (3) Results: The AI-driven immune assays, Immunoscore (IS) and Immunoscore-Immune Checkpoint (IS-IC), have emerged as powerful tools for improving cancer diagnosis, prognosis, and treatment selection by assessing the tumor immune contexture in cancer patients. Digital IS quantitative assessment performed on hematoxylin-eosin (H&E) and CD3+/CD8+ stained slides from colon cancer patients has proven to be more reproducible, concordant, and reliable than expert pathologists' evaluation of immune response. Outperforming traditional staging systems, IS demonstrated robust potential to enhance treatment efficiency in clinical practice, ultimately advancing cancer patient care. Certainly, addressing the challenges DP has encountered is essential to ensure its successful integration into clinical guidelines and its implementation into clinical use. (4) Conclusion: The ongoing progress in DP holds the potential to revolutionize pathology practices, emphasizing the need to incorporate powerful AI technologies, including IS, into clinical settings to enhance personalized cancer therapy.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.