AI Medical Compendium Journal:
Frontiers in big data

Showing 11 to 15 of 15 articles

CTAB-GAN+: enhancing tabular data synthesis.

Frontiers in big data
The usage of synthetic data is gaining momentum in part due to the unavailability of original data due to privacy and legal considerations and in part due to its utility as an augmentation to the authentic data. Generative adversarial networks (GANs)...

Enhancing knowledge discovery from unstructured data using a deep learning approach to support subsurface modeling predictions.

Frontiers in big data
Subsurface interpretations and models rely on knowledge from subject matter experts who utilize unstructured information from images, maps, cross sections, and other products to provide context to measured data (e. g., cores, well logs, seismic surve...

Non-invasive detection of anemia using lip mucosa images transfer learning convolutional neural networks.

Frontiers in big data
Anemia is defined as a drop in the number of erythrocytes or hemoglobin concentration below normal levels in healthy people. The increase in paleness of the skin might vary based on the color of the skin, although there is currently no quantifiable m...

Parallel Operators for High Performance Data Science and Data Engineering.

Frontiers in big data
Data-intensive applications are becoming commonplace in all science disciplines. They are comprised of a rich set of sub-domains such as data engineering, deep learning, and machine learning. These applications are built around efficient data abstrac...

Runoff Forecasting Using Machine-Learning Methods: Case Study in the Middle Reaches of Xijiang River.

Frontiers in big data
Runoff forecasting is useful for flood early warning and water resource management. In this study, backpropagation (BP) neural network, generalized regression neural network (GRNN), extreme learning machine (ELM), and wavelet neural network (WNN) mod...