A diffusion-weighted MRI radiomics model combined with clinical variables demonstrated strong predictive accuracy for progression-free survival in hypopharyngeal cancer patients ...
An editorial in Frontiers in Oncology reviews how AI and multi-omics are transforming breast cancer treatment response prediction and prognostic ...
A hybrid framework combining convolutional neural networks, vision transformers, and handcrafted radiomics achieved high diagnostic accuracy across differing mammography datasets.
A multicenter study demonstrates that deep learning and hybrid models analyzing preoperative magnetic resonance imaging can identify medulloblastoma molecular subgroups ...
Professor Philippe Lambin delivered a special lecture at Korea University College of Medicine outlining the future of medical artificial intelligence, ...
A pilot study of 14 metastatic prostate cancer patients indicates that machine learning models combining PSMA PET radiomics and clinical ...
An interpretable machine learning model utilizing CT radiomics and dosimetric parameters predicted radiation pneumonitis in breast cancer patients with an ...
A combined ultrasound radiomics and deep learning model preoperatively predicted axillary lymph node metastatic burden in breast cancer patients.
Integrating population-specific skeletal muscle thresholds with CT radiomic texture features and clinical indicators significantly improved postoperative survival risk stratification in ...
Discover Imaging has launched as a fully open access journal dedicated to multidisciplinary imaging research, spanning fundamental modalities, artificial intelligence ...
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