In the Cox proportional hazards regression model, which is the most commonly used model in survival analysis, the effects of independent variables on survival may not be constant over time and proportionality cannot be achieved, especially when long-...
BACKGROUND: The purpose of this study was to create a nomogram using machine learning models predicting risk of breast reconstruction complications with or without postmastectomy radiation therapy.
OBJECTIVE: We aimed to develop a deep learning-based signature to predict prognosis and benefit from adjuvant chemotherapy using preoperative computed tomography (CT) images.
Mathematical biosciences and engineering : MBE
Jul 16, 2021
The purpose of this study was to explore whether the Nomogram, which was constructed by combining the Deep learning and Radiomic features of T2-weighted MR images with Clinical factors (NDRC), could accurately predict placenta invasion. This retrospe...
BACKGROUND: Biparametric MRI (comprising T2-weighted MRI and apparent diffusion coefficient maps) is increasingly being used to characterise prostate cancer. Although previous studies have combined Prostate Imaging-Reporting & Data System (PI-RADS)-b...
Journal of vascular and interventional radiology : JVIR
Mar 1, 2019
PURPOSE: To construct the albumin-bilirubin (ALBI) grade and the Child-Turcotte-Pugh (CTP) score based on nomograms, as well as to develop an artificial neural network (ANN) to compare the prognostic performance of the 2 scores for hepatocellular car...
Studies in health technology and informatics
Jan 1, 2017
This study objectives to investigate a range of Partin table and several machine learning methods for pathological stage prediction and assess them with respect to their predictive model performance based on Koreans data. The data was used SPCDB and ...
Preoperatively predict the probability of Prostate cancer (PCa) biochemical recurrence (BCR) is of definite clinical relevance. The purpose of this study was to develop an imaging-based approach in the prediction of 3-years BCR through a novel suppor...
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