Structured illumination microscopy (SIM) has become an important technique for optical super-resolution imaging because it allows a doubling of image resolution at speeds compatible with live-cell imaging. However, the...
Structured illumination microscopy (SIM) has become an important technique for
optical super-resolution imaging because it allows a doubling of image resolution at speeds
compatible with live-cell imaging. However, the...
A multi-label variant of email classification named ML-EC2 (multi-label email classification using clustering) has been proposed in this work. ML-EC2 is a hybrid algorithm based on text clustering, text classification...
BACKGROUND: Drain insertion following chronic subdural hematoma (CSDH) evacuation improves patient outcomes. OBJECTIVE: To examine whether this is influenced by variation in drain location, positioning or duration of placement....
Artificial intelligence (AI) integration, notably in healthcare, has been significant, yet effective implementation in critical areas requires expertise. KoopaML, a previously developed visual platform, aims at bridging this...
BACKGROUND: Drain insertion following chronic subdural haematoma (CSDH) evacuation reduces recurrence and improves outcomes. The mechanism of this improvement is uncertain. We assessed whether drains result in improved...
According to the market research firm Tractica, the global artificial intelligence software market is forecast to grow to 126 billion by 2025. Additionally, the Gartner group predicts that during the same time as much as 80% of...
A reporter group method was developed in order to obtain information about small changes in the environment at specific positions in protein molecules. In this method one environmentally sensitive group is introduced into a...
AbstractUsing machine learning (ML) method to predict permeability of porous media has shown great potential in recent years. A current problem is the lack of effective models to...
AbstractUsing machine learning (ML) method to predict permeability of porous media has shown great potential in recent years. A current problem is the lack of effective models to...
A new method for the continuous measurement of low rates of oxygen production is described, which is useful for the study of photosynthetic systems. An inert carrier gas flows at a controlled rate through a cuvette, then over a...
Abstract: Using machine learning (ML) method to predict permeability of porous media has shown great potential in recent years. A current problem is the lack of effective models to account for highly porous media with dilated...
Connected vehicular tracking schema operated in environmentally safe radio frequency of 434 MHz, artificial intelligence, and machine learning and IoT technology (CVT-AIML-IoT) is cost effective and secured tracking or device...
Clustering of variables is a specialized approach for dimensionality reduction. This strategy is evaluated for data reduction with a Kaggle diabetes dataset. Since the original dataset is small, Generative Adversarial Networks...
In our interconnected world, the use of Internet of Things (IoT) devices generates vast amounts of sensitive data. To secure this data while extracting insights, privacy-preserving machine learning (PPML) tools like Fully...
We use a Lagrangian chemical transport model with a Monte-Carlo approach to determine impacts of kinetic rate uncertainties on simulated concentrations of ozone, NOy and OH in a high-altitude biomass burning plume and...
Background: Despite being frequently landed in fish markets along the Saudi Arabian Red Sea coast, information regarding fundamental biology of the Scalloped hammerhead shark (Sphyrna lewini) in this region is scarce. Satellite...
AIM: To estimate the effects of wine glass size on volume of wine sold in bars and restaurants. DESIGN: A mega-analysis combining raw (as opposed to aggregate-level) data from eight studies conducted in five establishments. A...