ArticlePrecision clinical medicine2023
Artificial intelligence-based non-invasive tumor segmentation, grade stratification and prognosis prediction for clear-cell renal-cell carcinoma.
Article in Precision clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 13 citations in OpenAlex.
- Artificial intelligence for evaluation of magnetic resonance imaging-detected extramural vascular invasion in rectal cancer.PLOS digital health · 2026Article
- MRI In Vivo Detection of Amyloid-β Protein Deposition in Different Brain Regions of Patients with AD and MCI.Brain topography · 2026Article
- Deciphering the mechanistic landscape of immune checkpoint blockade in ccRCC: from molecular drivers to therapeutic responses.Frontiers in immunology · 2026Review
- The irreplaceable role of pathology for the clinical translation of patient-derived organoids in precision medicine.Precision clinical medicine · 2025Article
- Computer vision assisted deep transfer learning model for accurate grading of renal cell carcinoma from kidney histopathology images.Scientific reports · 2025Article
- Artificial Intelligence in Nephrology: From Early Detection to Clinical Management of Kidney Diseases.Bioengineering (Basel, Switzerland) · 2025Review
- Glycosylation in kidney diseases.Precision clinical medicine · 2025Review
- Integrating quantitative DCE-MRI parameters and radiomic features for improved IDH mutation prediction in gliomas.Frontiers in oncology · 2025Article
- Metabolic reprogramming in clear cell renal cell carcinoma: core pathways and targeted therapeutic strategies.Frontiers in genetics · 2025Review
- Comparative analysis of tertiary lymphoid structures for predicting survival of colorectal cancer: a whole-slide images-based study.Precision clinical medicine · 2024Article
- Automation of Wilms' tumor segmentation by artificial intelligence.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
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Authors and funding
14 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Due to the complicated histopathological characteristics of clear-cell renal-cell carcinoma (ccRCC), non-invasive prognosis before operative treatment is crucial in selecting the appropriate treatment. A total of 126 345 computerized tomography (CT) images from four independent patient cohorts were included for analysis in this study. We propose a V Bottleneck multi-resolution and focus-organ network (VB-MrFo-Net) using a cascade framework for deep learning analysis. The VB-MrFo-Net achieved better performance than VB-Net in tumor segmentation, with a Dice score of 0.87. The nuclear-grade prediction model performed best in the logistic regression classifier, with area under curve values from 0.782 to 0.746. Survival analysis revealed that our prediction model could significantly distinguish patients with high survival risk, with a hazard ratio (HR) of 2.49 [95% confidence interval (CI): 1.13-5.45,
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