BACKGROUND: P53 mutation status is a pivotal biomarker for gliomas. Here, we developed a machine-learning model to predict p53 status in lower-grade gliomas based on radiomic features extracted from conventional magnetic resonance (MR) images.
BACKGROUND: Recently published data support the use of a web-based risk calculator ( www.anastomoticleak.com ) for the prediction of anastomotic leak after colectomy. The aim of this study was to externally validate this calculator on a larger datase...
BACKGROUND: Diet is one of the pillars of the treatment for patients with chronic kidney disease without dialysis (NDD-CKD). Despite this, very few studies have evaluated the diet in Spanish population.
The American journal of the medical sciences
Oct 26, 2017
BACKGROUND: Growing evidence suggest that macrophage migration inhibitory factor (MIF) plays a vital role in glucose metabolism. We aimed to ascertain whether MIF levels are altered in subjects with prediabetes and also to determine the relationship ...
OBJECTIVES: To explore the application value and forensic significance of ischemia modified albumin （IMA） in pericardial fluid to diagnose sudden cardiac death.
IEEE journal of biomedical and health informatics
Oct 23, 2017
The estimation of long-term diabetes complications risk is essential in the process of medical decision making. Guidelines for the management of Type 2 Diabetes Mellitus (T2DM) advocate calculating the Cardiovascular Disease (CVD) risk to initiate ap...
Purpose To investigate diagnostic performance by using a deep learning method with a convolutional neural network (CNN) for the differentiation of liver masses at dynamic contrast agent-enhanced computed tomography (CT). Materials and Methods This cl...
Computational intelligence and neuroscience
Oct 19, 2017
Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. Th...
OBJECTIVES: This study evaluated the added predictive value of combining clinical information and myocardial perfusion single-photon emission computed tomography (SPECT) imaging (MPI) data using machine learning (ML) to predict major adverse cardiac ...
Purpose To develop a machine learning model that allows high-risk breast lesions (HRLs) diagnosed with image-guided needle biopsy that require surgical excision to be distinguished from HRLs that are at low risk for upgrade to cancer at surgery and t...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.