ArticleJournal of healthcare informatics research2025
Multimodal Data Fusion for Whole-Slide Histopathology Image Classification.
Article in Journal of healthcare informatics research, 2025. 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
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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.
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.
- Swarm intelligence-guided ROI selection for deep learning assessment of HER2 in colorectal cancer.Scientific reports · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Whole slide images (WSIs) are critical for cancer diagnosis but pose computational challenges due to their gigapixel resolution. While automated AI tools can accelerate diagnostic workflows, they often rely on precise annotations and require substantial training data. Integrating multimodal data-such as WSIs and corresponding pathology reports-offers a promising solution to improve classification accuracy and reduce diagnostic variability. In this study, we introduce MPath-Net, an end-to-end multimodal framework that combines WSIs and pathology reports for enhanced cancer subtype classification. Using the TCGA dataset (1684 cases: 916 kidney, 768 lung), we applied multiple-instance learning (MIL) for WSI feature extraction and Sentence-BERT for report encoding, followed by joint fine-tuning for tumor classification. MPath-Net achieved 94.65% accuracy, 0.9553 precision, 0.9472 recall, and 0.9473 F1-score, significantly outperforming baseline models (
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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 Socratic graph.