AIMC Topic: Algorithms

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Separation of Different Blogs from Skin Disease Data using Artificial Intelligence.

Computational intelligence and neuroscience
A combination of environmental conditions may cause skin illness everywhere on the earth, and it is one of the most dangerous diseases that can develop as a result. A major goal in the selection of characteristics is to produce predictions about skin...

Research on a Machine Learning-Based Method for Assessing the Safety State of Historic Buildings.

Computational intelligence and neuroscience
Historic and protected buildings are increasingly valued due to their valuable historical and cultural value. The assessment of the safety state of historic buildings has received more attention. Emerging machine learning algorithms, with their excel...

Aerial Separation and Receiver Arrangements on Identifying Lung Syndromes Using the Artificial Neural Network.

Computational intelligence and neuroscience
Lung disease is one of the most harmful diseases in traditional days and is the same nowadays. Early detection is one of the most crucial ways to prevent a human from developing these types of diseases. Many researchers are involved in finding variou...

Few-Shot Learning for Image-Based Nonintrusive Appliance Signal Recognition.

Computational intelligence and neuroscience
In this article, we present the recognition of nonintrusive disaggregated appliance signals through a reduced dataset computer vision deep learning approach. Deep learning data requirements are costly in terms of acquisition time, storage memory requ...

Situation Element Extraction Based on Fuzzy Rough Set and Combination Classifier.

Computational intelligence and neuroscience
Generalized network security situation awareness technology is divided into three processes: situation element extraction, situation understanding, and situation prediction. Situation element extraction is the most critical step in the whole process,...

Deep Convolutional Neural Network Mechanism Assessment of COVID-19 Severity.

BioMed research international
As an epidemic, COVID-19's core test instrument still has serious flaws. To improve the present condition, all capabilities and tools available in this field are being used to combat the pandemic. Because of the contagious characteristics of the uniq...

Effect of Intelligent Medical Data Technology in Postoperative Nursing Care.

BioMed research international
Surgery is one of the larger wounds in conventional surgery, and patients often experience different pain and postural discomfort after surgery. With the ever-changing standards of medical care and patient care requirements, providing high-quality ca...

A novel hybrid approach for feature selection enhancement: COVID-19 case study.

Computer methods in biomechanics and biomedical engineering
Feature selection is a promising Artificial Intelligence technique for screening, analysing, predicting, and tracking current COVID-19 patients and likely future patients. Significant applications are developed to track data of confirmed, recovered, ...

Integrating model explanations and hybrid priors into deep stacked networks for the "safe zone" prediction of acetabular cup.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Existing state-of-the-art "safe zone" prediction methods are statistics-based methods, image-matching techniques, and machine learning methods. Yet, those methods bring a tension between accuracy and interpretability.

Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms.

Journal of digital imaging
The main aim of the present study was to predict myocardial function improvement in cardiac MR (LGE-CMR) images in patients after coronary artery bypass grafting (CABG) using radiomics and machine learning algorithms. Altogether, 43 patients who had ...