PURPOSE: Accurate clinical diagnosis of lymph node metastases is of paramount importance in the treatment of patients with abdominopelvic malignancy. This review assesses the diagnostic performance of deep learning algorithms and radiomics models for...
Recurrence risk stratification of patients undergoing primary surgical resection for hepatocellular carcinoma (HCC) is an area of active investigation, and several staging systems have been proposed to optimize treatment strategies. However, as many ...
Approximately 30% of medulloblastoma (MB) patients exhibit metastasis at initial diagnosis, which often leads to a poor prognosis. Here, by using univariate Cox regression analysis, two machine learning methods (Lasso-penalized Cox regression and ran...
AJR. American journal of roentgenology
Oct 14, 2020
The purpose of this study was to develop an effective nomogram and artificial neural network (ANN) model for predicting recurrent hemoptysis after bronchial artery embolization (BAE). The institutional ethics review boards of the two participating ...
BACKGROUND: Preoperative diagnoses of metastatic lymph nodes (LNs) by the most advanced deep learning technology of Faster Region-based Convolutional Neural Network (Faster R-CNN) have not yet been reported.
The mechanisms underlying the resistance to immune checkpoint inhibitors (ICIs) therapy in metastatic urothelial carcinoma (mUC) patients are not clear. It is of great significance to discern mUC patients who could benefit from ICI therapy in clinica...
We sought to identify the factors associated with deterioration of renal functions after robot-assisted radical cystectomy, and to develop a nomogram to detect the probability of progression to chronic kidney disease (CKD). A retrospective review o...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jul 4, 2020
PURPOSE: To estimate the prognostic value of deep learning (DL) magnetic resonance (MR)-based radiomics for stage T3N1M0 nasopharyngeal carcinoma (NPC) patients receiving induction chemotherapy (ICT) prior to concurrent chemoradiotherapy (CCRT).
OBJECTIVES: To evaluate the differential diagnostic performance of a computed tomography (CT)-based deep learning nomogram (DLN) in identifying tuberculous granuloma (TBG) and lung adenocarcinoma (LAC) presenting as solitary solid pulmonary nodules (...
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