International journal of biometeorology
Feb 28, 2023
AquaCrop is one of the dynamic and user-friendly models for simulating different conditions governing plant growth in the field. But this model requires many input parameters such as plant information, soil, climate, groundwater, and management facto...
IEEE transactions on neural networks and learning systems
Feb 28, 2023
Convolutional neural networks (CNNs) are widely used in the field of medical imaging diagnosis but have the disadvantages of slow training speed and low diagnostic accuracy due to the initialization of parameters before training. In this article, a C...
International journal of environmental research and public health
Feb 28, 2023
In the last few years, many types of research have been conducted on the most harmful pandemic, COVID-19. Machine learning approaches have been applied to investigate chest X-rays of COVID-19 patients in many respects. This study focuses on the deep ...
Car networking systems based on 5G-V2X (vehicle-to-everything) have high requirements for reliability and low-latency communication to further improve communication performance. In the V2X scenario, this article establishes an extended model (basic e...
With the phenomenal rise in internet-of-things devices, the use of electroencephalogram (EEG) based brain-computer interfaces (BCIs) can empower individuals to control equipment with thoughts. These allow BCI to be used and pave the way for pro-activ...
PURPOSE: To develop a truly calibrationless reconstruction method that derives An Eigenvalue Approach to Autocalibrating Parallel MRI (ESPIRiT) maps from uniformly-undersampled multi-channel MR data by deep learning.
Cardiovascular engineering and technology
Feb 27, 2023
PURPOSE: Computed tomography coronary angiography (CCTA) images provide optimal visualization of coronary arteries to aid in diagnosing coronary heart disease (CHD). With the deep convolutional neural network, this work aims to develop an intelligent...
PURPOSE: To perform a comprehensive intraindividual objective and subjective image quality evaluation of coronary CT angiography (CCTA) reconstructed with deep learning image reconstruction (DLIR) and to assess correlation with routinely applied hybr...
INTRODUCTION: We aimed to develop an artificial intelligence (AI) deep learning algorithm to efficiently estimate placental and fetal volumes from magnetic resonance (MR) scans.
Due to technological developments, wearable sensors for monitoring the behavior of farm animals have become cheaper, have a longer lifespan and are more accessible for small farms and researchers. In addition, advancements in deep machine learning me...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.