A systematic review and meta-analysis shows that lung ultrasound offers high sensitivity and moderate specificity for detecting rheumatoid arthritis-associated interstitial ...
Lobar classical radiomics from combined inspiratory and expiratory CT scans outperformed handcrafted measures in detecting chronic airflow limitation in a ...
A retrospective cohort study of 375 breast cancer patients found that pre-treatment cardiac calcium burden and radiation doses to the ...
A new deep learning framework called CLAHE-RATSNet improves lung nodule segmentation in CT images by combining image enhancement with a ...
A retrospective study in BMC Pulmonary Medicine found that CT-derived surface area is significantly associated with invasive pathology in surgically ...
A novel sectional deep learning framework with region normalization improves hepatocellular carcinoma detection and staging accuracy from computed tomography scans.
A cost-utility analysis in Thailand finds that PET-CT is most cost-effective and carries the lowest budget impact when used solely ...
Integrating automated three-dimensional body composition radiomics with tumor features significantly improved postoperative overall survival prediction in patients with resectable non-small ...
A scoping review of 50 articles finds that automated CT scoring for cystic fibrosis and primary ciliary dyskinesia remains limited ...
A retrospective cohort study found that FDG-PET detected heterogeneous treatment responses in thirty percent of metastatic breast cancer follow-up examinations, ...
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