ReviewPflugers Archiv : European journal of physiology2025
Decoding pathology: the role of computational pathology in research and diagnostics.
Review in Pflugers Archiv : European journal of physiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Article
- Compositional and interpretable representation of histology using AI foundation models and sparse autoencoders.bioRxiv : the preprint server for biology · 2026Article
- Artificial intelligence in small tissue biopsies: diagnostic applications, histochemical integration, and methodological challenges in surgical pathology.Histochemistry and cell biology · 2026Review
- Benchmarking multiple instance learning architectures from patches to pathology for prostate cancer detection and grading using attention-based weak supervision.Scientific reports · 2026Article
- PMI estimation with cross-species transfer learning and visual information generated by pathomics foundation model.International journal of legal medicine · 2026Article
- HiGATE: hierarchical graph attention for multi-scale tissue encoder in computational pathology.Frontiers in oncology · 2026Article
- Artificial intelligence in membranous nephropathy: transforming clinical management toward precision medicine.Frontiers in medicine · 2026Review
- PathQC: Determining Molecular and Structural Integrity of Tissues from Histopathological Slides.Bioengineering (Basel, Switzerland) · 2025Article
- Uncertainty-aware and causal test-time adaptive foundation model for robust colorectal cancer pathology diagnosis.NPJ digital medicine · 2025Article
- Special issue European Journal of Physiology: Artificial intelligence in the field of physiology and medicine.Pflugers Archiv : European journal of physiology · 2025Article
- MDL-CA: a multimodal deep learning approach with a cross attention mechanism for accurate brain cancer diagnosis.Frontiers in public health · 2025Article
- AI in Cytopathology: A Narrative Umbrella Review on Innovations, Challenges, and Future Directions.Journal of clinical medicine · 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
2 authors.
Funding
Abstract
Traditional histopathology, characterized by manual quantifications and assessments, faces challenges such as low-throughput and inter-observer variability that hinder the introduction of precision medicine in pathology diagnostics and research. The advent of digital pathology allowed the introduction of computational pathology, a discipline that leverages computational methods, especially based on deep learning (DL) techniques, to analyze histopathology specimens. A growing body of research shows impressive performances of DL-based models in pathology for a multitude of tasks, such as mutation prediction, large-scale pathomics analyses, or prognosis prediction. New approaches integrate multimodal data sources and increasingly rely on multi-purpose foundation models. This review provides an introductory overview of advancements in computational pathology and discusses their implications for the future of histopathology in research and diagnostics.
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.