Deep Learning CT Volumetry Enhances Consistency in Pulmonary Nodule Assessment
A deep learning segmentation tool significantly improves observer agreement and lowers false-positive classifications in lung cancer screening assessments.
A deep learning segmentation tool significantly improves observer agreement and lowers false-positive classifications in lung cancer screening assessments.
Clinicians successfully used emergency endoscopy to treat an esophageal perforation and septic shock caused by an impacted bone while managing ...
A retrospective study shows that quantified baseline ascites volume above 613.5 milliliters independently predicts significantly reduced survival in patients receiving ...
A retrospective single-centre study of obese adults undergoing lumbar spinal fusion found a 71.4 percent fusion rate alongside elevated acute ...
A multimodal artificial intelligence framework combining CT scans, pathology slides, and tumor microenvironment markers improved survival risk prediction after surgery ...
A retrospective analysis of 183 ureteroscopic procedures found that stone volume, density, and renal location were significantly associated with total ...
A retrospective study of 15 surgical patients shows that pancreatic colloid carcinoma presents with characteristic cystic-solid morphology and progressive delayed ...
A prospective comparative study shows that FAPI-46 PET/CT significantly improves the detection of postoperative lymph node metastases in papillary thyroid ...
A systematic review of ninety-six pediatric cases alongside an illustrative clinical report demonstrates that gross total resection is achieved in ...
A comprehensive review reveals that deep learning artificial intelligence systems achieve over ninety percent accuracy in bladder cancer detection, though ...
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© 2026 Scienmag - Science Magazine