ReviewCureus2024
Transforming Diagnostics: A Comprehensive Review of Advances in Digital Pathology.
Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Revolutionizing personalized medicine using artificial intelligence: a meta-analysis of predictive diagnostics and their impacts on drug development.Clinical and experimental medicine · 2025Pooled it
- Digital Pathology in Dermatology - Current Status, Applications and Perspectives.Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG · 2026Review
- Review
- An artificial intelligence solution for evaluation of prostate needle core biopsy specimens: impact in a non-specialist setting.Virchows Archiv : an international journal of pathology · 2026Article
- Advances in Avian Diagnostic Pathology: Current Trends, Challenges and Future Directions: A Review.Veterinary medicine and science · 2026Review
- Intraoperative video-based artificial intelligence model exceeding surgeon accuracy for predicting severe fibrosis in minimally invasive liver surgery.Scientific reports · 2026Article
- Intelligent Stain-Free Histology on Structural Colorimetric Nanocavities.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- AI and the digital pathology revolution: clinical applications in cancer diagnosis and assessment.Expert review of molecular diagnostics · 2026Review
- Digital pathology platforms with integrated AI algorithms: a structured landscape analysis and recommendations for clinical implementation.Virchows Archiv : an international journal of pathology · 2026Article
- Toward a regional digital pathology network in Tuscany: current status and implementation roadmap.Virchows Archiv : an international journal of pathology · 2026Article
- The impact of AI on modern oncology from early detection to personalized cancer treatment.NPJ precision oncology · 2026Review
- Foundation models in computational pathology: methods, applications and clinical implications.BMJ oncology · 2026Review
- Leveraging digital pathology to enhance breast cancer diagnosis in low-resource settings: a cross-sectional study of major histopathology laboratories in Uganda.Oxford open digital health · 2026Article
- Wesselsbron Virus-Induced Hepatitis in Ewes and Lambs Unraveled Through Machine Learning-Driven Digital Histopathology.Transboundary and emerging diseases · 2026Article
- The role of artificial intelligence-based foundation models and "copilots" in cancer pathology: potential and challenges.Journal of experimental & clinical cancer research : CR · 2025Review
- Current Trends and Future Directions of Digital Pathology and Artificial Intelligence in Dermatopathology: A Scientometric-Based Review.Diagnostics (Basel, Switzerland) · 2025Review
- Digital Pathology Tailored for Assessment of Liver Biopsies.Biomedicines · 2025Article
- Innovative approach for the qualitative-quantitative assessment of neurodevelopment biomarkers research in placenta tissue using immunohistochemistry digital image analysis.Biology methods & protocols · 2025Article
- Pathology in the artificial intelligence era: Guiding innovation and implementation to preserve human insight.Academic pathologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital pathology has emerged as a revolutionary field, transforming traditional diagnostic practices by integrating advanced imaging technologies, computational tools, and artificial intelligence (AI). Adopting digital slides over conventional glass slides enables high-resolution imaging, facilitating remote consultations, second opinions, and telepathology. The digitalization of pathology laboratories enhances workflow efficiency and allows for large-scale data storage, retrieval, and analysis, paving the way for developing robust diagnostic algorithms. One of the most transformative aspects of digital pathology is its synergy with AI and machine learning (ML). These technologies have enabled the automation of repetitive processes, including diseased feature detection, biomarker quantification, and tissue segmentation. This has decreased inter-observer variability and increased diagnostic accuracy. AI-driven algorithms are particularly beneficial in complex cases, assisting pathologists in detecting subtle patterns that might be missed through manual examination. Furthermore, digital pathology plays a critical role in personalized medicine by enabling the precise characterization of tumors, which leads to targeted therapy decisions. Integrating digital pathology with genomics and other omics data holds promise for a more holistic understanding of diseases, driving innovation in diagnostics and treatment. However, the transition to digital pathology is challenging. Issues such as data standardization, regulatory compliance, and the need for robust IT infrastructure must be addressed to realize its full potential. This review provides a detailed examination of these advances, their clinical applications, and the challenges faced in the widespread adoption of digital pathology. As the field continues to evolve, it is poised to play a pivotal role in shaping the future of diagnostics, offering new possibilities for improving patient outcomes. This comprehensive review explores the significant advances in digital pathology, highlighting its impact on diagnostics, research, and patient care.
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What OpenQuestion 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 OpenQuestion graph.