PET/CT model helps distinguish primary lung cancer from colorectal metastasis
A combined model of 18F-FDG PET/CT parameters and clinical risk factors achieved an AUC of 0.871 in distinguishing primary lung ...
A combined model of 18F-FDG PET/CT parameters and clinical risk factors achieved an AUC of 0.871 in distinguishing primary lung ...
A stool-based machine learning model combining gut archaea, bacteria, fungi, viruses and microbial genes detected cholangiocarcinoma with an average AUC ...
A retrospective case-control study from a single Chinese hospital built an internally validated machine learning model using six routine blood ...
A multi-phase MRI deep learning model combined with clinical predictors differentiated hepatocellular carcinoma from mass-forming intrahepatic cholangiocarcinoma with AUCs of ...
A retrospective study found that CT venous-phase radiomics models, led by logistic regression, distinguished early from advanced gastric cancer with ...
A bioinformatics study identified six downregulated mitochondrial genes as candidate diagnostic biomarkers for the scarring kidney disease FSGS, supported by ...
A multicenter retrospective study developed a nomogram using four routine blood parameters that outperformed conventional serum indices for detecting significant ...
A LightGBM-based diagnostic model was developed and validated in a multicenter retrospective study to improve the timely identification and risk ...
A machine-learning model based on six serum proteins diagnosed esophageal squamous cell carcinoma with AUCs of 0.932 and 0.968 in ...
A five-marker RNA-based tissue model developed by Chinese researchers distinguished benign from malignant breast lesions with an internal-validation accuracy of ...
© 2025 Scienmag - Science Magazine
© 2025 Scienmag - Science Magazine