ArticleJournal of pathology informatics2013
Applying perceptual and adaptive learning techniques for teaching introductory histopathology.
Article in Journal of pathology informatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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
27 citing papers in PubMed.
- Perceptual learning enhances diabetic retinopathy detection skills in novice optometry students.BMC medical education · 2026Trial
- The impact of a perceptual learning module on novices' ability to visually estimate left ventricular ejection fraction by transesophageal echocardiography: a randomized controlled study.Canadian journal of anaesthesia = Journal canadien d'anesthesie · 2021Trial
- Hypothetical Abductive Reasoning in Dermatology and Dermatopathology.Dermatopathology (Basel, Switzerland) · 2025Article
- Development of CytoAcademy: a new web- and mobile-based E-learning platform for cytopathologists and cytotechnologists by the Korean Society for Cytopathology in the post-pandemic era.Journal of pathology and translational medicine · 2024Review
- The effects of procedural and conceptual knowledge on visual learning.Advances in health sciences education : theory and practice · 2024Article
- From Image to Diagnosis: Characterizing Sources of Error in Histopathologic Interpretation.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2023Article
- Connecting Adaptive Perceptual Learning and Signal Detection Theory in Skin Cancer Screening.CogSci ... Annual Conference of the Cognitive Science Society. Cognitive Science Society (U.S.). Conference · 2023Article
- Evaluating the effectiveness of different perceptual training methods in a difficult visual discrimination task with ultrasound images.Cognitive research: principles and implications · 2023Article
- Multiple expressions of "expert" abnormality gist in novices following perceptual learning.Cognitive research: principles and implications · 2023Article
- Effects of visual art observation on technical skills in novice healthcare learners: A scoping review.F1000Research · 2023Article
- Novel Diagnostic Educational Resource: Use of a web-based adaptive learning module to teach inflammatory reaction patterns in dermatopathology to medical students, residents, and fellows.Journal of pathology informatics · 2022Article
- Mastering Electrocardiogram Interpretation Skills Through a Perceptual and Adaptive Learning Module.AEM education and training · 2021Article
- Evaluating the Use of Supplemental Training Technologies in Dermatology Education.Journal of dermatology for physician assistants : Official journal of the Society of Dermatology Physician Assistants · 2021Article
- What do radiologists look for? Advances and limitations of perceptual learning in radiologic search.Journal of vision · 2020Review
- Transient cholinergic enhancement does not significantly affect either the magnitude or selectivity of perceptual learning of visual texture discrimination.Journal of vision · 2020Article
- Use of an Adaptive e-Learning Platform as a Formative Assessment Tool in the Cardiovascular System Course Component of an MBBS Programme.Advances in medical education and practice · 2020Article
- Analysis of Perceptual Expertise in Radiology - Current Knowledge and a New Perspective.Frontiers in human neuroscience · 2019Review
- Accelerating expertise: Perceptual and adaptive learning technology in medical learning.Medical teacher · 2018Article
- Visualization of vascular injuries in extremity trauma.Medical & biological engineering & computing · 2017Article
- Perceptual training to improve hip fracture identification in conventional radiographs.PloS one · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundMedical students are expected to master the ability to interpret histopathologic images, a difficult and time-consuming process. A major problem is the issue of transferring information learned from one example of a particular pathology to a new example. Recent advances in cognitive science have identified new approaches to address this problem.
methodsWe adapted a new approach for enhancing pattern recognition of basic pathologic processes in skin histopathology images that utilizes perceptual learning techniques, allowing learners to see relevant structure in novel cases along with adaptive learning algorithms that space and sequence different categories (e.g. diagnoses) that appear during a learning session based on each learner's accuracy and response time (RT). We developed a perceptual and adaptive learning module (PALM) that utilized 261 unique images of cell injury, inflammation, neoplasia, or normal histology at low and high magnification. Accuracy and RT were tracked and integrated into a "Score" that reflected students rapid recognition of the pathologies and pre- and post-tests were given to assess the effectiveness.
resultsAccuracy, RT and Scores significantly improved from the pre- to post-test with Scores showing much greater improvement than accuracy alone. Delayed post-tests with previously unseen cases, given after 6-7 weeks, showed a decline in accuracy relative to the post-test for 1(st)-year students, but not significantly so for 2(nd)-year students. However, the delayed post-test scores maintained a significant and large improvement relative to those of the pre-test for both 1(st) and 2(nd) year students suggesting good retention of pattern recognition. Student evaluations were very favorable.
conclusionA web-based learning module based on the principles of cognitive science showed an evidence for improved recognition of histopathology patterns by medical students.
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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.