ReviewFrontiers in digital health2024
Digital pathology implementation in cancer diagnostics: towards informed decision-making.
Review in Frontiers in digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Global research trends and hotspots in robotic-assisted prostate biopsy: a bibliometric analysis from 2008 to 2026.Journal of robotic surgery · 2026Article
- The patient matters: a roundtable discussion on pathology in the era of digitization and AI.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
- Machine learning for extracellular vesicles enables diagnostic and therapeutic nanobiotechnology.Journal of nanobiotechnology · 2026Review
- Advancing Doctoral and Postdoctoral International Bioethics Training Programs Supported by the D43 National Institutes of Health (NIH) Fogarty Mechanism.Journal of empirical research on human research ethics : JERHRE · 2025Article
- Fogarty-Funded Research Ethics Training Programs in Eastern Europe.Journal of empirical research on human research ethics : JERHRE · 2025Article
- Digital Pathology Tailored for Assessment of Liver Biopsies.Biomedicines · 2025Article
- Ethical principles across countries: does 'ethical' mean the same everywhere?Frontiers in public health · 2025Review
- Transforming cervical cancer pathological diagnosis through artificial intelligence: progress, performance, and barriers to clinical implementation.Frontiers in oncology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital pathology (DP) has become a part of the cancer healthcare system, creating additional value for cancer patients. DP implementation in clinical practice provides plenty of benefits but also harbors hidden ethical challenges affecting physician-patient relationships. This paper addresses the ethical obligation to transform the physician-patient relationship for informed and responsible decision-making when using artificial intelligence (AI)-based tools for cancer diagnostics. DP application allows to improve the performance of the Human-AI Team shifting focus from AI challenges towards the Augmented Human Intelligence (AHI) benefits. AHI enhances analytical sensitivity and empowers pathologists to deliver accurate diagnoses and assess predictive biomarkers for further personalized treatment of cancer patients. At the same time, patients' right to know about using AI tools, their accuracy, strengths and limitations, measures for privacy protection, acceptance of privacy concerns and legal protection defines the duty of physicians to provide the relevant information about AHI-based solutions to patients and the community for building transparency, understanding and trust, respecting patients' autonomy and empowering informed decision-making in oncology.
Indexed as
Identifiers
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.