ReviewHead and neck pathology2026
Artificial Intelligence Basics for Head and Neck Pathologists: A Simple Guide.
Review in Head and neck pathology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
Artificial intelligence (AI) is reshaping pathology practice by assisting pathologists in analyzing and interpreting complex tissue and cellular imaging data. AI offers new opportunities to enhance accuracy, efficiency, and consistency in histopathological evaluation and lesion diagnosis. This perspective provides a simple guide for head and neck pathologists on the fundamentals and applications of AI. It outlines the main categories and concepts of AI, describes the basic workflow of model development, and highlights its utilization in head and neck pathology. This article also summarizes key AI terminologies with examples specific to this field, discusses the evolving role of pathologists in AI development and deployment, and underscores the challenges and considerations involved in integrating AI into routine practice. Importantly, AI should be viewed not as a substitute for human expertise but as a complemental tool to reduce interobserver variability, shorten turnaround times, and help manage the growing diagnostic workload in pathology laboratories. Algorithms are only as reliable as the data and context in which they are developed. The active involvement of pathologists remains critical to ensuring diagnostic accuracy, patient safety, and high-quality, patient-centered care in head and neck pathology.
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.