Latest AI and machine learning research in medicaid for healthcare professionals.
BACKGROUND: Persistent significant proteinuria has been associated with increased risk of progressio...
The valuable structure features in full-dose computed tomography (FdCT) scans can be exploited as pr...
Creative solutions are needed to support community-dwelling older adults residing in a variety of se...
Dose reduction in computed tomography (CT) is essential for decreasing radiation risk in clinical ap...
We propose a robust Alternating Low-Rank Representation (ALRR) model formed by an alternating forwar...
This paper presents a novel approach for evaluating LBP in various settings. The proposed system use...
OBJECTIVES: This study aimed to provide an empirical model of predicting low back pain (LBP) by cons...
There have been a lot of methods to address the recognition of complete face images. However, in rea...
Automatic feature extraction and classification are two main tasks in abnormal ECG beat recognition....
Deep learning-based radiomics (DLR) was developed to extract deep information from multiple modaliti...
OBJECTIVE: Active surveillance (AS) offers a strategy to reduce overtreatment and now is a widely ac...
In the past decades, bioassays and whole-organism bioassay have become important tools not only in c...
Given the potential risk of X-ray radiation to the patient, low-dose CT has attracted a considerable...
This work proposed a novel automatic three-dimensional (3D) magnetic resonance imaging (MRI) segment...
Many structural variations (SVs) detection methods have been proposed due to the popularization of n...
A low-cost robotic interface was used to assess the visuo-motor performance of patients with Alzheim...
Drug repositioning has been a key problem in drug development, and heterogeneous data sources are us...
OBJECTIVE: Despite high-grade intravesical prostatic protrusion (IPP) being closely related to bladd...
PURPOSE: Few investigations of robot-assisted intersphincteric resection (ISR) are presently availab...
Semisupervised Discriminant Analysis (SDA) is a semisupervised dimensionality reduction algorithm, w...
In recent years, sparse and low-rank models have been widely used to formulate appearance subspace f...