ArticleAcademic pathology
Pathology in the artificial intelligence era: Guiding innovation and implementation to preserve human insight.
Article in Academic pathology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed.
- AI In Leukemia Diagnostics: Complementing the Pathologist's Role.International journal of laboratory hematology · 2026Review
- Agentic systems in computational pathology: architectures, evidence, and translational challenges.Journal of translational medicine · 2026Review
- Accelerating the implementation of digital pathology in India.Journal of pathology informatics · 2026Review
- Pathology-derived clinical micro-architectural diagnostics of tumour-microbiome interactions in colorectal cancer.Journal of translational medicine · 2026Article
- Blended and digital approaches in histology and pathology teaching: A scoping review.Anatomical sciences education · 2026Article
- AI-assisted fibrosis scoring in MASH: Exploring pathologist decision-making with an SHG-based AI digital pathology tool.JHEP reports : innovation in hepatology · 2026Article
- Clarifying validation terminologies in healthcare.NPJ digital medicine · 2026Article
- Toward a regional digital pathology network in Tuscany: current status and implementation roadmap.Virchows Archiv : an international journal of pathology · 2026Article
- The actual and future role of molecular tests in thyroid pathology.Virchows Archiv : an international journal of pathology · 2026Review
- Artificial intelligence in genitourinary pathology.Histopathology · 2026Review
- Multimodal artificial intelligence and machine learning in oncology: from data integration to precision cancer care.Frontiers in digital health · 2026Review
- Digital Pathology with AI for Cervical Biopsies: Diagnostic Accuracy at the CIN2+ Threshold.Cancers · 2025Article
- Artificial Intelligence in Oncology: A 10-Year ClinicalTrials.gov-Based Analysis Across the Cancer Control Continuum.Cancers · 2025Review
- The Rise of AI-Assisted Diagnosis: Will Pathologists Be Partners or Bystanders?Diagnostics (Basel, Switzerland) · 2025Review
- Artificial Intelligence in the Diagnostic Use of Transcranial Doppler and Sonography: A Scoping Review of Current Applications and Future Directions.Bioengineering (Basel, Switzerland) · 2025Review
- Leveraging digital pathology and AI to transform clinical diagnosis in developing countries.Frontiers in medicine · 2025Article
- Review
- Bridging Medicine and Dentistry Through Clinical Pathology: A Call for Integration.Sage open pathologyArticle
- Evaluating artificial intelligence-generated multiple-choice questions in clinical pathology.Academic pathologyArticle
- Strength, weakness, opportunities and challenges (SWOC) experience of histopathology image analysis, enhanced by artificial intelligence.Journal of oral biology and craniofacial researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The integration of artificial intelligence in pathology has ignited discussions about the role of technology in diagnostics-whether artificial intelligence serves as a tool for augmentation or risks replacing human expertise. This manuscript explores artificial intelligence's evolving contributions to pathology, emphasizing its potential capacity to enhance, rather than eclipse, the pathologist's role. Through historical comparisons, such as the transition from analog to digital in radiology, this paper highlights how technological advancements have historically expanded professional capabilities without diminishing the essential human element. Current applications of artificial intelligence in pathology-from diagnostic standardization to workflow efficiency-demonstrate its potential to augment diagnostic accuracy, expedite processes, and improve consistency across institutions. However, challenges remain in algorithmic bias, regulatory oversight, and maintaining interpretive skills among pathologists. The discussion underscores the importance of comprehensive governance frameworks, evolving educational curricula, and public engagement initiatives to ensure artificial intelligence in pathology remains a collaborative endeavor that empowers professionals, upholds ethical standards, and enhances patient outcomes. This manuscript ultimately advocates for a balanced approach where artificial intelligence and human expertise work in concert to advance the future of diagnostic medicine.
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.