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MPANet: Deep Learning Outperforms Radiologists in Renal Tumor Classification
A multimodal deep learning model called MPANet significantly outperforms radiologists at classifying renal tumors from multiphase CT imaging, achieving 73.3% accuracy compared to 43.6-62.4% for specialist assessments. Original paper: Multimodal deep learning model for multiclass classification of renal tumors. — NPJ digital medicine. 10.1038/s41746-026-02697-0 📄 Read the article
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By MedAI DigestA multimodal deep learning model called MPANet significantly outperforms radiologists at classifying renal tumors from multiphase CT imaging, achieving 73.3% accuracy compared to 43.6-62.4% for specialist assessments. Original paper: Multimodal deep learning model for multiclass classification of renal tumors. — NPJ digital medicine. 10.1038/s41746-026-02697-0 📄 Read the article