ArticlePloS one2015
Pigeons (Columba livia) as Trainable Observers of Pathology and Radiology Breast Cancer Images.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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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.
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Who cites it
34 citing papers in PubMed, 99 citations in OpenAlex.
- Neural representation of object category and viewpoint in the entopallium of pigeons.Zoological research · 2026Article
- Behavioral characteristics of rapid visual categorization learning in domestic chicks.Learning & behavior · 2026Article
- Multidimensional visual feature encoding and functional organization in the pigeon entopallium.Zoological research · 2026Article
- An animal model of radiological medical image reading: detection of lung abnormalities in multi-slice CT by pigeons (Columba livia).Animal cognition · 2026Article
- The cost of unmodeled biological complexity in artificial neural networks.Patterns (New York, N.Y.) · 2025Review
- Categorization of echocardiograms by humans and pigeons.Frontiers in psychology · 2025Article
- Human reinforcement learning processes and biases: computational characterization and possible applications to behavioral public policy.Mind & society · 2025Article
- The effects of procedural and conceptual knowledge on visual learning.Advances in health sciences education : theory and practice · 2024Article
- No evidence of real-world equivalence in chickens (Gallus gallus domesticus) categorizing visually diverse images of natural stimuli presented on LCD monitors.Learning & behavior · 2024Article
- Precision diagnostics in transplanted organs using microarray-assessed gene expression: concepts and technical methods of the Molecular Microscope® Diagnostic System (MMDx).Clinical science (London, England : 1979) · 2024Review
- Jackdaws form categorical prototypes based on experience with category exemplars.Brain structure & function · 2024Article
- Current Landscape of Advanced Imaging Tools for Pathology Diagnostics.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2024Review
- Long-term, high-resolution in vivo calcium imaging in pigeons.Cell reports methods · 2024Article
- The pigeon as a machine: Complex category structures can be acquired by a simple associative model.iScience · 2023Article
- Eagle eyed or bird brained?Eye (London, England) · 2023Review
- AI in Pathology: What could possibly go wrong?Seminars in diagnostic pathology · 2023Review
- Using global feedback to induce learning of gist of abnormality in mammograms.Cognitive research: principles and implications · 2023Article
- Article
- Visual categories and concepts in the avian brain.Animal cognition · 2023Review
- Digital embryos: a novel technical approach to investigate perceptual categorization in pigeons (Columba livia) using machine learning.Animal cognition · 2022Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pathologists and radiologists spend years acquiring and refining their medically essential visual skills, so it is of considerable interest to understand how this process actually unfolds and what image features and properties are critical for accurate diagnostic performance. Key insights into human behavioral tasks can often be obtained by using appropriate animal models. We report here that pigeons (Columba livia)-which share many visual system properties with humans-can serve as promising surrogate observers of medical images, a capability not previously documented. The birds proved to have a remarkable ability to distinguish benign from malignant human breast histopathology after training with differential food reinforcement; even more importantly, the pigeons were able to generalize what they had learned when confronted with novel image sets. The birds' histological accuracy, like that of humans, was modestly affected by the presence or absence of color as well as by degrees of image compression, but these impacts could be ameliorated with further training. Turning to radiology, the birds proved to be similarly capable of detecting cancer-relevant microcalcifications on mammogram images. However, when given a different (and for humans quite difficult) task-namely, classification of suspicious mammographic densities (masses)-the pigeons proved to be capable only of image memorization and were unable to successfully generalize when shown novel examples. The birds' successes and difficulties suggest that pigeons are well-suited to help us better understand human medical image perception, and may also prove useful in performance assessment and development of medical imaging hardware, image processing, and image analysis tools.
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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.