AI Medical Compendium Journal:
Big data

Showing 21 to 30 of 80 articles

Prescreening and Triage of COVID-19 Patients Through Chest X-Ray Images Using Deep Learning Model.

Big data
Deep learning models deliver a fast diagnosis during triage prescreening for COVID-19 patients, reducing waiting time for hospital admission during health emergency scenarios. The Ministry of health and family welfare government of India provides gui...

Forecasting Subway Passenger Flow for Station-Level Service Supply.

Big data
Demand forecasting is one of the managers' concerns in service supply chain management. With accurate passenger flow forecasting, the station-level service suppliers can make better service plans accordingly. However, the existing forecasting model c...

Optimization of Imbalanced and Multidimensional Learning Under Bayes Minimum Risk and Savings Measure.

Big data
The full potential of data analysis is crippled by imbalanced and high-dimensional data, which makes these topics significantly important. Consequently, substantial research efforts have been directed to obtain dimension reduction and resolve data im...

A Network Intrusion Detection System Using Hybrid Multilayer Deep Learning Model.

Big data
An intrusion detection system (IDS) is designed to detect and analyze network traffic for suspicious activity. Several methods have been introduced in the literature for IDSs; however, due to a large amount of data, these models have failed to achiev...

Predicting Social Events with Multimodal Fusion of Spatial and Temporal Dynamic Graph Representations.

Big data
Big data has been satisfactorily used to solve social issues in several parts of the word. Social event prediction is related to social stability and sustainable development. However, current research rarely takes into account the dynamic connections...

Predicting Actions of Users Using Heterogeneous Online Signals.

Big data
Advertising platforms have a growing need for improving prediction quality, as missing out on ad opportunities can have a negative effect on their performance. To that end, prediction tasks such as conversion prediction need to be continuously advanc...

An Empirical Evaluation of Network Representation Learning Methods.

Big data
Network representation learning methods map network nodes to vectors in an embedding space that can preserve specific properties and enable traditional downstream prediction tasks. The quality of the representations learned is then generally showcase...

DGSLSTM: Deep Gated Stacked Long Short-Term Memory Neural Network for Traffic Flow Forecasting of Transportation Networks on Big Data Environment.

Big data
Deep learning and big data techniques have become increasingly popular in traffic flow forecasting. Deep neural networks have also been applied to traffic flow forecasting. Furthermore, it is difficult to determine whether neural networks can be used...

Hybrid Deep Learning Approach for Traffic Speed Prediction.

Big data
Traffic speed prediction plays a fundamental role in traffic management and driving route planning. However, timely accurate traffic speed prediction is challenging as it is affected by complex spatial and temporal correlations. Most existing works c...

Service Level Agreement Monitoring as a Service: An Independent Monitoring Service for Service Level Agreements in Clouds.

Big data
The cloud network is rapidly growing due to a massive increase in interconnected devices and the emergence of different technologies such as the Internet of things, fog computing, and artificial intelligence. In response, cloud computing needs reliab...