PURPOSE: Artificial intelligence is part of our daily life and machine learning techniques offer possibilities unknown until now in medicine. This study aims to offer an evaluation of the performance of machine learning (ML) techniques, for predictin...
The objective of this research was to investigate the application values of magnetic resonance imaging (MRI) features of the deep learning-based image super-resolution reconstruction algorithm optimized convolutional neural network (OPCNN) algorithm ...
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
May 23, 2022
OBJECTIVES: We aimed to design a radiomics model for differential diagnosis of thyroid carcinoma based on dynamic ultrasound video, and compare its diagnostic performance with that of radiomics model based on static ultrasound images.
The aim of the study described here was to investigate the value of different machine learning models based on the clinical and radiomic features of 2-D ultrasound images to evaluate post-transplant renal function (pTRF). We included 233 patients who...
PURPOSE: Automated retinal vessel segmentation is crucial to the early diagnosis and treatment of ophthalmological diseases. Many deep-learning-based methods have shown exceptional success in this task. However, current approaches are still inadequat...
OBJECTIVE: Analyzing pressure injury (PI) risk factors is complex because of multiplicity of associated factors and the multidimensional nature of this injury. The main objective of this study was to identify patients at risk of developing PI.
Continuous monitoring of high-risk patients and early prediction of severe outcomes is crucial to prevent avoidable deaths. Current clinical monitoring is primarily based on intermittent observation of vital signs and the early warning scores (EWS). ...
Our objective was to develop deep learning models with chest radiograph data to predict healthcare costs and classify top-50% spenders. 21,872 frontal chest radiographs were retrospectively collected from 19,524 patients with at least 1-year spending...
BACKGROUND: The debate of whether machine learning models offer advantages over standard statistical methods when making predictions is ongoing. We discuss the use of a meta-learner model combining both approaches as an alternative.