ArticleDigital health
Diagnostic digital pathology implementation: Learning from the digital health experience.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed, 50 citations in OpenAlex.
- The patient matters: a roundtable discussion on pathology in the era of digitization and AI.Virchows Archiv : an international journal of pathology · 2026Article
- 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
- Current Trends and Future Directions of Digital Pathology and Artificial Intelligence in Dermatopathology: A Scientometric-Based Review.Diagnostics (Basel, Switzerland) · 2025Review
- 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
- Article
- An update on applications of digital pathology: primary diagnosis; telepathology, education and research.Diagnostic pathology · 2025Review
- The Impact of Artificial Intelligence on Cancer Diagnosis and Treatment: A Review.Cancer informatics · 2025Review
- A deep learning model to predict Ki-67 positivity in oral squamous cell carcinoma.Journal of pathology informatics · 2024Article
- Crossing the Andes: Challenges and opportunities for digital pathology in Latin America.Journal of pathology informatics · 2024Review
- Staff Experiences Transitioning to Digital Dermatopathology in a Tertiary Academic Medical Center: Lessons Learned From Implementation Science.Mayo Clinic proceedings. Digital health · 2024Article
- [Digital transformation of a routine histopathology lab : Dos and don'ts!]Pathologie (Heidelberg, Germany) · 2024Review
- Digital pathology implementation in cancer diagnostics: towards informed decision-making.Frontiers in digital health · 2024Review
- Rapid Deployment of Whole Slide Imaging for Primary Diagnosis in Surgical Pathology at Stanford Medicine: Responding to Challenges of the COVID-19 Pandemic.Archives of pathology & laboratory medicine · 2023Article
- Sustainable development goals applied to digital pathology and artificial intelligence applications in low- to middle-income countries.Frontiers in medicine · 2023Article
- Quantitative melanoma diagnosis using spectral phasor analysis of hyperspectral imaging from label-free slices.Frontiers in oncology · 2023Article
- Machine Learning-Based Classification of Abnormal Liver Tissues Using Relative Permittivity.Sensors (Basel, Switzerland) · 2022Article
- Review
- Digital Pathology Implementation in Private Practice: Specific Challenges and Opportunities.Diagnostics (Basel, Switzerland) · 2022Article
- Establishment of a whole slide imaging-based frozen section service at a cancer center.Journal of pathology informatics · 2022Article
- Contemporary Whole Slide Imaging Devices and Their Applications within the Modern Pathology Department: A Selected Hardware Review.Journal of pathology informatics · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital Pathology (also referred to as Telepathology and Whole Slide Imaging) is the process of producing high resolution digital images from tissue sections on glass slides. These glass slides are normally examined under a microscope by a pathologist as part of the diagnostic process. The emergence of digital pathology now means that digital images are stored on secure servers and can be viewed on computer monitors; enabling pathologists to work remotely and to collaborate with other colleagues when second opinions are needed. The implementation of digital pathology into clinical practice has many potential benefits. Although this has been long recognised, its adoption as a diagnostic tool remains low and pathologists' projections about its future deployment are cautious. Notable early digital pathology adopters have led the way. The challenge now is to scale-up digital pathology beyond the relatively few large networks and centres of excellence. Many other areas of healthcare have accumulated experience about optimising approaches to digital health/healthcare technology deployment and sustainability. This has been done in a multi-disciplinary context and has applied theoretical/conceptual frameworks. Thus far there has been little use of similar frameworks in the planning of digital pathology deployment in clinical practice. In this essay, I will explore the scope of digital pathology implementation approaches that have been deployed in clinical practice and examine what can be learned from the wider healthcare experience of adopting, scaling-up and sustaining innovative healthcare solutions.
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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.