AIMC Topic: Algorithms

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Classification of BCI Multiclass Motor Imagery Task Based on Artificial Neural Network.

Clinical EEG and neuroscience
Motor imagery (MI) signals recorded by electroencephalography provide the most practical basis for conceiving brain-computer interfaces (BCI). These interfaces offer a high degree of freedom. This helps people with motor disabilities communicate with...

Artificial Intelligence for Detecting Cephalometric Landmarks: A Systematic Review and Meta-analysis.

Journal of digital imaging
Using computer vision through artificial intelligence (AI) is one of the main technological advances in dentistry. However, the existing literature on the practical application of AI for detecting cephalometric landmarks of orthodontic interest in di...

Hybrid attention-based temporal convolutional bidirectional LSTM approach for wind speed interval prediction.

Environmental science and pollution research international
Precise wind speed prediction is crucial for the management of the wind power generation systems. However, the stochastic nature of the wind speed makes optimal interval prediction very complicated. In this paper, a hybrid approach consisting of impr...

Survey of Explainable AI Techniques in Healthcare.

Sensors (Basel, Switzerland)
Artificial intelligence (AI) with deep learning models has been widely applied in numerous domains, including medical imaging and healthcare tasks. In the medical field, any judgment or decision is fraught with risk. A doctor will carefully judge whe...

An Insight into the Machine-Learning-Based Fileless Malware Detection.

Sensors (Basel, Switzerland)
In recent years, massive development in the malware industry changed the entire landscape for malware development. Therefore, cybercriminals became more sophisticated by advancing their development techniques from file-based to fileless malware. As f...

Gradient Tree Boosting for Hierarchical Data.

Multivariate behavioral research
Gradient tree boosting is a powerful machine learning technique that has shown good performance in predicting a variety of outcomes. However, when applied to hierarchical (e.g., longitudinal or clustered) data, the predictive performance of gradient ...

Systematic Review of Advanced AI Methods for Improving Healthcare Data Quality in Post COVID-19 Era.

IEEE reviews in biomedical engineering
At the beginning of the COVID-19 pandemic, there was significant hype about the potential impact of artificial intelligence (AI) tools in combatting COVID-19 on diagnosis, prognosis, or surveillance. However, AI tools have not yet been widely success...

Unsupervised ECG Analysis: A Review.

IEEE reviews in biomedical engineering
Electrocardiography is the gold standard technique for detecting abnormal heart conditions. Automatic detection of electrocardiogram (ECG) abnormalities helps clinicians analyze the large amount of data produced daily by cardiac monitors. As thenumbe...

Graph Signal Processing, Graph Neural Network and Graph Learning on Biological Data: A Systematic Review.

IEEE reviews in biomedical engineering
Graph networks can model data observed across different levels of biological systems that span from population graphs (with patients as network nodes) to molecular graphs that involve omics data. Graph-based approaches have shed light on decoding bio...

Computational pathology in 2030: a Delphi study forecasting the role of AI in pathology within the next decade.

EBioMedicine
BACKGROUND: Artificial intelligence (AI) is rapidly fuelling a fundamental transformation in the practice of pathology. However, clinical integration remains challenging, with no AI algorithms to date in routine adoption within typical anatomic patho...