AIMC Topic: Algorithms

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Authentication with a one-dimensional CNN model using EEG-based brain-computer interface.

Computer methods in biomechanics and biomedical engineering
Brain-computer interface (BCI) technology uses electroencephalogram (EEG) signals to create a direct interaction between the human body and its surroundings. Motor imagery (MI) classification using EEG signals is an important application that can hel...

Clinical applications of deep learning in neuroinflammatory diseases: A scoping review.

Revue neurologique
BACKGROUND: Deep learning (DL) is an artificial intelligence technology that has aroused much excitement for predictive medicine due to its ability to process raw data modalities such as images, text, and time series of signals.

Evaluation of different machine learning algorithms for extraction decision in orthodontic treatment.

Orthodontics & craniofacial research
INTRODUCTION: The extraction decision significantly affects the treatment process and outcome. Therefore, it is crucial to make this decision with a more objective and standardized method. The objectives of this study were (1) to identify the best-pe...

Fragmentomics features of ovarian cancer.

International journal of cancer
Ovarian cancer (OC) is a major cause of cancer mortality in women worldwide. Due to the occult onset of OC, its nonspecific clinical symptoms in the early phase, and a lack of effective early diagnostic tools, most OC patients are diagnosed at an adv...

Enhancing cancer prediction in challenging screen-detected incident lung nodules using time-series deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Lung cancer screening (LCS) using annual computed tomography (CT) scanning significantly reduces mortality by detecting cancerous lung nodules at an earlier stage. Deep learning algorithms can improve nodule malignancy risk stratification. However, t...

Prototype-based sample-weighted distillation unified framework adapted to missing modality sentiment analysis.

Neural networks : the official journal of the International Neural Network Society
Missing modality sentiment analysis is a prevalent and challenging issue in real life. Furthermore, the heterogeneity of multimodality often leads to an imbalance in optimization when attempting to optimize the same objective across all modalities in...

Active Dynamic Weighting for multi-domain adaptation.

Neural networks : the official journal of the International Neural Network Society
Multi-source unsupervised domain adaptation aims to transfer knowledge from multiple labeled source domains to an unlabeled target domain. Existing methods either seek a mixture of distributions across various domains or combine multiple single-sourc...

Unsupervised domain adaptive segmentation algorithm based on two-level category alignment.

Neural networks : the official journal of the International Neural Network Society
To enhance the model's generalization ability in unsupervised domain adaptive segmentation tasks, most approaches have primarily focused on pixel-level local features, but neglected the clue in category information. This limitation results in the seg...

A robust multi-scale feature extraction framework with dual memory module for multivariate time series anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Although existing reconstruction-based multivariate time series anomaly detection (MTSAD) methods have shown advanced performance, most assume the training data is clean. When faced with noise or contamination in training data, they can also reconstr...

Automatic height measurement of central serous chorioretinopathy lesion using a deep learning and adaptive gradient threshold based cascading strategy.

Computers in biology and medicine
Accurately quantifying the height of central serous chorioretinopathy (CSCR) lesion is of great significance for assisting ophthalmologists in diagnosing CSCR and evaluating treatment efficacy. The manual measurement results dominated by single optic...