ArticleHeliyon2024
Improving the accuracy of reporting Ki-67 IHC by using an AI tool.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Article
- Retrospective Validation of a Resource-Aware Assistive AI Tool for Screening Prostate Needle Biopsies and Classifying Prostate Adenocarcinoma into ISUP Grade Groups.Life (Basel, Switzerland) · 2026Article
- Assessment of the Correlation between Macroscopic ICRS Grading and Histopathological OARSI Scoring in Osteoarthritic Cartilage: AnCartilage · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ki-67 proliferative index (PI) scoring is measured by estimating the proportion of the number of active cell nuclei in hotspot regions within immunohistochemical (IHC) stained slides. It provides valuable information about the rate of proliferation in a tumour. Manual scoring of Ki-67 PI is laborious, time-consuming and often the victim of interobserver variability between pathologists. This motivated us to develop an AI-based method to automate Ki-67 PI scoring with the aim to improve the concordance of pathologists' inter-observability through aided diagnosis. We sourced 88 sequential cases of sarcomas for our study. We applied watershed algorithm to perform nuclear segmentation on 440 regions of interest (ROI). A study was conducted where three pathologists scored the Ki-67 PI on the ROIs with and without AI-assistance. Our study demonstrated great concordance between the pathologists scoring with AI-assistance. After AI assistance, inter-pathologist discordance was significantly reduced by 82.1.
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.