ArticleNature communications2024
A multi-classifier system integrated by clinico-histology-genomic analysis for predicting recurrence of papillary renal cell carcinoma.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
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- A Deep Learning-Based Multimodal Clinico-Histology-Genomic Prognostic Model in Prostate Cancer.Annals of surgical oncology · 2026Article
- Mitochondrial apoptosis gene-based pathomics for ovarian cancer prognosis.Scientific reports · 2026Article
- Comprehensive review of publicly accessible databases for gastrointestinal cancer and future challenges in database construction.Discover oncology · 2026Review
- Artificial intelligence in genitourinary pathology.Histopathology · 2026Review
- The Emerging Role of Multimodal Artificial Intelligence in Urological Surgery.Current oncology (Toronto, Ont.) · 2025Review
- Tumor cell- and infiltrating immune cell-based supervised learning artificial intelligence multimodal platform for tumor prognosis.NPJ precision oncology · 2025Article
- Effect of immune-related intratumoral microbiota and host gene expression on cancer prognosis.mSystems · 2025Article
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- From static to dynamic: Artificial intelligence revolution in perioperative care through multimodal data fusion and closed-loop optimization.Journal of anesthesia and translational medicine · 2025Review
- Comparative analysis of clinicopathological characteristics and prognostic outcomes in fumarate hydratase-deficient renal cell carcinoma versus high-grade papillary renal cell carcinoma.Translational andrology and urology · 2025Article
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- Aging-Associated CD55⁺ Fibroblasts Promote Chronic Inflammation and ECM Dysregulation in Sarcopenia.Journal of inflammation research · 2025Article
- Intraoperative change in distal motor latency as a predictor for clinical outcome after mini-OCTR: a retrospective cohort study.Frontiers in neurology · 2025Article
- [Performance of multi-modality and multi-classifier fusion models for predicting radiation-induced oral mucositis in patients with nasopharyngeal carcinoma].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024Article
- A multi-classifier system integrated by clinico-histology-genomic analysis for predicting recurrence of papillary renal cell carcinoma.Nature communications · 2024Article
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41 authors.
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Abstract
Integrating genomics and histology for cancer prognosis demonstrates promise. Here, we develop a multi-classifier system integrating a lncRNA-based classifier, a deep learning whole-slide-image-based classifier, and a clinicopathological classifier to accurately predict post-surgery localized (stage I-III) papillary renal cell carcinoma (pRCC) recurrence. The multi-classifier system demonstrates significantly higher predictive accuracy for recurrence-free survival (RFS) compared to the three single classifiers alone in the training set and in both validation sets (C-index 0.831-0.858 vs. 0.642-0.777, p < 0.05). The RFS in our multi-classifier-defined high-risk stage I/II and grade 1/2 groups is significantly worse than in the low-risk stage III and grade 3/4 groups (p < 0.05). Our multi-classifier system is a practical and reliable predictor for recurrence of localized pRCC after surgery that can be used with the current staging system to more accurately predict disease course and inform strategies for individualized adjuvant therapy.
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