ArticleBMC research notes2026
PathoTiroid dataset: Indonesian collection (PTIC)-a histopathology image dataset for papillary thyroid carcinoma.
Article in BMC research notes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- PathoTiroid dataset: Indonesian collection (PTIC)-a histopathology image dataset for papillary thyroid carcinoma.BMC research notes · 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
7 authors.
Funding
Abstract
objectivesThe dataset was created to support reproducible artificial intelligence (AI) model development and benchmarking in papillary thyroid carcinoma (PTC) histopathology research. This dataset was generated as part of a broader research project focused on building and evaluating deep learning models for the classification of PTC. It addresses a specific gap in the availability of high-quality, image-level annotated histopathology datasets for thyroid cancer, especially those derived from underrepresented populations in Southeast Asia. The dataset is designed to be reusable for various AI downstream tasks, including classification, domain adaptation, stain normalization, and model interpretability in thyroid pathology. DATA DESCRIPTION: The PathoTiroid Dataset – Indonesian Collection (PTIC) dataset is a curated and expert-validated dataset of PTC histopathology images acquired from Indonesia’s national referral hospital. The dataset comprises 1,006 high-resolution images extracted from 46 whole-slide images (WSIs). A rigorous multistage validation process was employed to minimize annotation noise and enhance the dataset’s utility for supervised deep learning applications. The dataset is structured into two main classes corresponding to the PTC-like and non-PTC-like categories. This dataset aims to enhance the development and evaluation of AI-based models for PTC identification, serving as a valuable benchmark for comparative studies in computational pathology.
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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.