Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic ...
Breast cancer screening has long been a target use case for artificial intelligence (AI). Developments in computational power ...
Model and clinical segmentation examples. (A) 71-year-old female with non-small cell lung cancer (NSCLC) from the internal test set. (B) 87-year-old male with NSCLC from the external test set. Both ...
Validation of LungFlag Lean machine-learning model to identify individuals with lung cancer using multinational data. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This ...
A deep-learning serial CT biomarker improves survival prediction in immunotherapy-treated NSCLC and outperforms RECIST. Find ...
Deep learning analysis of FDG PET-CT improves survival prediction in non-metastatic breast cancer, outperforming standard staging and single modality models while supporting interpretable and ...
More and more thoracic CT scans are being performed worldwide in order to detect lung diseases such as bronchial carcinoma and tumor metastases at an early stage and allow them to be monitored. In ...
Ensemble integrating three architectures achieved area under the curve of 0.9208, outperforming individual models ...
A new paper in Biology Methods and Protocols, published by Oxford University Press, shows that scientists can train artificial intelligence models to distinguish brain tumors from healthy tissue. AI ...
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Diagnostic prognostic and therapeutic relevance of PIVKA-II in hepatocellular carcinoma
Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, particularly in regions with ...
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