AIMC Topic: Algorithms

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Research on Information Visualization Graphic Design Teaching Based on DBN Algorithm.

Computational intelligence and neuroscience
With the advent of the era of big data, how to quickly obtain effective information and efficiently disseminate information technology has become the most popular topic. Studies have shown that the ability of the human brain to process data and infor...

Video Abnormal Event Detection Based on One-Class Neural Network.

Computational intelligence and neuroscience
Video abnormal event detection is a challenging problem in pattern recognition field. Existing methods usually design the two steps of video feature extraction and anomaly detection model establishment independently, which leads to the failure to ach...

Identifying peripheral arterial disease in the elderly patients using machine-learning algorithms.

Aging clinical and experimental research
BACKGROUND: Peripheral artery disease (PAD) is a common syndrome in elderly people. Recently, artificial intelligence (AI) algorithms, in particular machine-learning algorithms, have been increasingly used in disease diagnosis.

Study on the identification of resistance of rice blast based on near infrared spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Rice Blast is the most devastating rice disease which poses a serious threat to the safe production of rice. The most effective way to prevent rice blast is to cultivate the rice varieties that have resistance to the disease, however, traditional res...

The value of human data annotation for machine learning based anomaly detection in environmental systems.

Water research
Anomaly detection is the process of identifying unexpected data samples in datasets. Automated anomaly detection is either performed using supervised machine learning models, which require a labelled dataset for their calibration, or unsupervised mod...

Exploring AdaBoost and Random Forests machine learning approaches for infrared pathology on unbalanced data sets.

The Analyst
The use of infrared spectroscopy to augment decision-making in histopathology is a promising direction for the diagnosis of many disease types. Hyperspectral images of healthy and diseased tissue, generated by infrared spectroscopy, are used to build...

XENet: Using a new graph convolution to accelerate the timeline for protein design on quantum computers.

PLoS computational biology
Graph representations are traditionally used to represent protein structures in sequence design protocols in which the protein backbone conformation is known. This infrequently extends to machine learning projects: existing graph convolution algorith...

Claims-based algorithms for common chronic conditions were efficiently constructed using machine learning methods.

PloS one
Identification of medical conditions using claims data is generally conducted with algorithms based on subject-matter knowledge. However, these claims-based algorithms (CBAs) are highly dependent on the knowledge level and not necessarily optimized f...

Explainable artificial intelligence for pharmacovigilance: What features are important when predicting adverse outcomes?

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Explainable Artificial Intelligence (XAI) has been identified as a viable method for determining the importance of features when making predictions using Machine Learning (ML) models. In this study, we created models that ta...

Static Attitude Determination Using Convolutional Neural Networks.

Sensors (Basel, Switzerland)
The need to estimate the orientation between frames of reference is crucial in spacecraft navigation. Robust algorithms for this type of problem have been built by following algebraic approaches, but data-driven solutions are becoming more appealing ...