AIMC Topic: Algorithms

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A predictive signal model for dynamic cardiac magnetic resonance imaging.

Scientific reports
Robust dynamic cardiac magnetic resonance imaging (MRI) has been a long-standing endeavor-as real-time imaging can provide information on the temporal signatures of disease we currently cannot assess-with the past decade seeing remarkable advances in...

ConvCoroNet: a deep convolutional neural network optimized with iterative thresholding algorithm for Covid-19 detection using chest X-ray images.

Journal of biomolecular structure & dynamics
Covid-19 is a global pandemic. Early and accurate detection of positive cases prevent the further spread of this epidemic and help to treat rapidly the infected patients. During the peak of this epidemic, there was an insufficiency of Covid-19 test k...

Development of a model for the prediction of biological age.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Rates of aging vary markedly among individuals, and biological age serves as a more reliable predictor of current health status than does chronological age. As such, the ability to predict biological age can support appropri...

Editorial: Generative artificial intelligence as a plagiarism problem.

Biological psychology
There is increasing concern and consternation about generative artificial intelligence (AI) programs and its potential impact on academia. This editorial addresses the potential impact of such programs on scientific publishing as it relates to the jo...

A Light-Weight Artificial Neural Network for Recognition of Activities of Daily Living.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) is essential for the development of robots to assist humans in daily activities. HAR is required to be accurate, fast and suitable for low-cost wearable devices to ensure portable and safe assistance. Current computat...

Modeling dissolved oxygen concentration using machine learning techniques with dimensionality reduction approach.

Environmental monitoring and assessment
Oxygen is crucial to keep the life cycle balance in any aspect. Aquatic life is highly influenced by the levels of dissolved oxygen (DO). This calls for not just constant monitoring of the DO in aquatic systems, but to generate an accurate prediction...

Stochastic momentum methods for non-convex learning without bounded assumptions.

Neural networks : the official journal of the International Neural Network Society
Stochastic momentum methods are widely used to solve stochastic optimization problems in machine learning. However, most of the existing theoretical analyses rely on either bounded assumptions or strong stepsize conditions. In this paper, we focus on...

Flood discharge prediction using improved ANFIS model combined with hybrid particle swarm optimisation and slime mould algorithm.

Environmental science and pollution research international
Due to the disastrous socio-economic impacts of flood hazards and estimated rise of its occurrences in the near future, there has been an increase in the importance of flood prediction worldwide. Artificial intelligence (AI) models have contributed s...

Artificial Intelligence Applied to a First Screening of Naevoid Melanoma: A New Use of Fast Random Forest Algorithm in Dermatopathology.

Current oncology (Toronto, Ont.)
Malignant melanoma (MM) is the "great mime" of dermatopathology, and it can present such rare variants that even the most experienced pathologist might miss or misdiagnose them. Naevoid melanoma (NM), which accounts for about 1% of all MM cases, is a...

Application of Machine Learning Algorithms for Tool Condition Monitoring in Milling Chipboard Process.

Sensors (Basel, Switzerland)
In this article, we present a novel approach to tool condition monitoring in the chipboard milling process using machine learning algorithms. The presented study aims to address the challenges of detecting tool wear and predicting tool failure in rea...