AIMC Topic: Software

Clear Filters Showing 1191 to 1200 of 3675 articles

Hybrid pointer networks for traveling salesman problems optimization.

PloS one
In this work, we proposed a hybrid pointer network (HPN), an end-to-end deep reinforcement learning architecture is provided to tackle the travelling salesman problem (TSP). HPN builds upon graph pointer networks, an extension of pointer networks wit...

Deep transformers and convolutional neural network in identifying DNA N6-methyladenine sites in cross-species genomes.

Methods (San Diego, Calif.)
As one of the most common post-transcriptional epigenetic modifications, N6-methyladenine (6 mA), plays an essential role in various cellular processes and disease pathogenesis. Therefore, accurately identifying 6 mA modifications is necessary for a ...

Protein embeddings and deep learning predict binding residues for various ligand classes.

Scientific reports
One important aspect of protein function is the binding of proteins to ligands, including small molecules, metal ions, and macromolecules such as DNA or RNA. Despite decades of experimental progress many binding sites remain obscure. Here, we propose...

Independent evaluation of 12 artificial intelligence solutions for the detection of tuberculosis.

Scientific reports
There have been few independent evaluations of computer-aided detection (CAD) software for tuberculosis (TB) screening, despite the rapidly expanding array of available CAD solutions. We developed a test library of chest X-ray (CXR) images which was ...

Using a convolutional neural network for classification of squamous and non-squamous non-small cell lung cancer based on diagnostic histopathology HES images.

Scientific reports
Histological stratification in metastatic non-small cell lung cancer (NSCLC) is essential to properly guide therapy. Morphological evaluation remains the basis for subtyping and is completed by additional immunohistochemistry labelling to confirm the...

Artificial intelligence based automatic quantification of epicardial adipose tissue suitable for large scale population studies.

Scientific reports
To develop a fully automatic model capable of reliably quantifying epicardial adipose tissue (EAT) volumes and attenuation in large scale population studies to investigate their relation to markers of cardiometabolic risk. Non-contrast cardiac CT ima...

Enhancing electrocardiographic analysis by combining a high-resolution 12-lead ECG with novel software tools.

Journal of electrocardiology
INTRODUCTION: Signal-averaged electrocardiography is a non-invasive, computerized technique that amplifies, filters, and averages cardiac electrical signals reducing contaminating noise to obtain a high-resolution record. The most widely used signal ...

Risk Prediction by Using Artificial Neural Network in Global Software Development.

Computational intelligence and neuroscience
The demand for global software development is growing. The nonavailability of software experts at one place or a country is the reason for the increase in the scope of global software development. Software developers who are located in different part...

Tools to support the automation of systematic reviews: a scoping review.

Journal of clinical epidemiology
OBJECTIVE: The objectives of this scoping review are to identify the reliability and validity of the available tools, their limitations and any recommendations to further improve the use of these tools.

EnTSSR: A Weighted Ensemble Learning Method to Impute Single-Cell RNA Sequencing Data.

IEEE/ACM transactions on computational biology and bioinformatics
The advancements of single-cell RNA sequencing (scRNA-seq) technologies have provided us unprecedented opportunities to characterize cellular states and investigate the mechanisms of complex diseases. Due to technical issues such as dropout events, s...