RATIONALE AND OBJECTIVES: Using different machine learning models CT-based radiomics to integrate clinical radiological features to discriminating the risk stratification of pheochromocytoma/paragangliomas (PPGLs).
OBJECTIVE: Increased subcutaneous and visceral adipose tissue (SAT/VAT) volume is associated with risk for cardiometabolic diseases. This work aimed to develop and evaluate automated abdominal SAT/VAT segmentation on longitudinal MRI in adults with o...
PURPOSE: Nearly all published ophthalmology-related Big Data studies rely exclusively on International Classification of Diseases (ICD) billing codes to identify patients with particular ocular conditions. However, inaccurate or nonspecific codes may...
Medical & biological engineering & computing
Feb 1, 2024
In this paper, we propose a new robust and fast learning technique by investigating the effect of integration of quaternion and interval type II fuzzy logic along with non-iterative, parameter free deterministic learning machine (DLM) pertaining to f...
Journal of minimally invasive gynecology
Feb 1, 2024
STUDY OBJECTIVE: Several simulation models have been evaluated for gynecologic procedures such as hysterectomy, but there are limited published data for myomectomy. This study aimed to assess the validity of a low-cost robotic myomectomy model for su...
BACKGROUND: Modic changes are pathologies that are common in the population and cause low back pain. The aim of the study is to analyze the modic changes detected in magnetic resonance imaging (MRI) using deep learning modalities.
COVID-19, known as Coronavirus Disease 2019 primarily targets the respiratory system and can impact the cardiovascular system, leading to a range of cardiorespiratory complications. The current forefront in analyzing the dynamical characteristics of ...
BACKGROUND AND OBJECTIVE: Machine learning (ML) is a subset of artificial intelligence that uses data to build algorithms to predict specific outcomes. Few ML studies have examined percutaneous nephrolithotomy (PCNL) outcomes. Our objective was to bu...
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Feb 1, 2024
BACKGROUND: We employed deep learning to automatically detect myocardial bone-seeking uptake as a marker of transthyretin cardiac amyloid cardiomyopathy (ATTR-CM) in patients undergoing 99mTc-pyrophosphate (PYP) or hydroxydiphosphonate (HDP) single-p...
Cigarette smoking during pregnancy is known to be associated with the incidence of attention-deficit/hyperactive disorder (ADHD). Recent developments in deep learning algorithms enable us to assess the behavioral phenotypes of animal models without c...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.