AIMC Topic: Algorithms

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Account of Deep Learning-Based Ultrasonic Image Feature in the Diagnosis of Severe Sepsis Complicated with Acute Kidney Injury.

Computational and mathematical methods in medicine
This study was aimed at analyzing the diagnostic value of convolutional neural network models on account of deep learning for severe sepsis complicated with acute kidney injury and providing an effective theoretical reference for the clinical use of ...

Interpretable Model Based on Pyramid Scene Parsing Features for Brain Tumor MRI Image Segmentation.

Computational and mathematical methods in medicine
Due to the black box model nature of convolutional neural networks, computer-aided diagnosis methods based on depth learning are usually poorly interpretable. Therefore, the diagnosis results obtained by these unexplained methods are difficult to gai...

Design of Automated Deep Learning-Based Fusion Model for Copy-Move Image Forgery Detection.

Computational intelligence and neuroscience
Due to the exponential growth of high-quality fake photos on social media and the Internet, it is critical to develop robust forgery detection tools. Traditional picture- and video-editing techniques include copying areas of the image, referred to as...

An improved X-means and isolation forest based methodology for network traffic anomaly detection.

PloS one
Anomaly detection in network traffic is becoming a challenging task due to the complexity of large-scale networks and the proliferation of various social network applications. In the actual industrial environment, only recently obtained unlabelled da...

Electrocardiogram Signal Classification in the Diagnosis of Heart Disease Based on RBF Neural Network.

Computational and mathematical methods in medicine
Heart disease is a common disease affecting human health. Electrocardiogram (ECG) classification is the most effective and direct method to detect heart disease, which is helpful to the diagnosis of most heart disease symptoms. At present, most ECG d...

Implementation and Optimization of Reverse Suspension Structure Design Model Using Deep Learning.

Computational intelligence and neuroscience
The present work aims to improve the design efficiency and optimize the results in the increasingly complex and diversified material design projects to help architects realize the better performance of building structures. According to the characteri...

Design of Financial Management Model Using the Forward Neural Network Based on Particle Swarm Optimization Algorithm.

Computational intelligence and neuroscience
The financial crisis of listed companies will bring huge losses to investors, so it is very important to establish a financial early warning model for investors and other stakeholders. The forward neural network model of particle swarm optimization i...

Developing Multiagent E-Learning System-Based Machine Learning and Feature Selection Techniques.

Computational intelligence and neuroscience
Recently, artificial intelligence (AI) domain increased to contain finance, education, health, mining, and education. Artificial intelligence controls the performance of systems that use new technologies, especially in the education environment. The ...

Improving the leak detection efficiency in water distribution networks using noise loggers.

The Science of the total environment
Leak detection techniques are effective ways of controlling water leakage in real water distribution networks (WDNs). Nevertheless, developing detection techniques for real WDNs has received little attention compared to the detection models developed...

Granger causality test with nonlinear neural-network-based methods: Python package and simulation study.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Causality defined by Granger in 1969 is a widely used concept, particularly in neuroscience and economics. As there is an increasing interest in nonlinear causality research, a Python package with a neural-network-based caus...