AIMC Topic: Algorithms

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Rethinking masked image modelling for medical image representation.

Medical image analysis
Masked Image Modelling (MIM), a form of self-supervised learning, has garnered significant success in computer vision by improving image representations using unannotated data. Traditional MIMs typically employ a strategy of random sampling across th...

Finite-time cluster synchronization of multi-weighted fractional-order coupled neural networks with and without impulsive effects.

Neural networks : the official journal of the International Neural Network Society
In this paper, finite-time cluster synchronization (FTCS) of multi-weighted fractional-order neural networks is studied. Firstly, a FTCS criterion of the considered neural networks is obtained by designing a new delayed state feedback controller. Sec...

Semantic segmentation in skin surface microscopic images with artifacts removal.

Computers in biology and medicine
Skin surface imaging has been used to examine skin lesions with a microscope for over a century and is commonly known as epiluminescence microscopy, dermatoscopy, or dermoscopy. Skin surface microscopy has been recommended to reduce the necessity of ...

An efficient colorectal cancer detection network using atrous convolution with coordinate attention transformer and histopathological images.

Scientific reports
The second most common type of malignant tumor worldwide is colorectal cancer. Histopathology image analysis offers crucial data for the clinical diagnosis of colorectal cancer. Currently, deep learning techniques are applied to enhance cancer classi...

Artificial Intelligence-Based Models for Prediction of Mortality in ICU Patients: A Scoping Review.

Journal of intensive care medicine
Background and ObjectiveHealthcare professionals may be able to anticipate more accurately a patient's timing of death and assess their possibility of recovery by implementing a real-time clinical decision support system. Using such a tool, the healt...

GTC: GNN-Transformer co-contrastive learning for self-supervised heterogeneous graph representation.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have emerged as the most powerful weapon for various graph tasks due to the message-passing mechanism's great local information aggregation ability. However, over-smoothing has always hindered GNNs from going deeper and c...

Validity of machine learning algorithms for automatically extract growing rod length on radiographs in children with early-onset scoliosis.

Medical & biological engineering & computing
The magnetically controlled growing rod technique is an effective surgical treatment for children who have early-onset scoliosis. The length of the instrumented growing rods is adjusted regularly to compensate for the normal growth of these patients....

The combined Lyapunov functionals method for stability analysis of neutral Cohen-Grossberg neural networks with multiple delays.

Neural networks : the official journal of the International Neural Network Society
This research article will employ the combined Lyapunov functionals method to deal with stability analysis of a more general type of Cohen-Grossberg neural networks which simultaneously involve constant time and neutral delay parameters. By utilizing...

COVID-19 IgG antibodies detection based on CNN-BiLSTM algorithm combined with fiber-optic dataset.

Journal of virological methods
The urgent need for efficient and accurate automated screening tools for COVID-19 detection has led to research efforts exploring various approaches. In this study, we present pioneering research on COVID-19 detection using a hybrid model that combin...

Combining artificial intelligence and conventional statistics to predict bronchopulmonary dysplasia in very preterm infants using routinely collected clinical variables.

Pediatric pulmonology
BACKGROUND: Prematurity is the strongest predictor of bronchopulmonary dysplasia (BPD). Most previous studies investigated additional risk factors by conventional statistics, while the few studies applying artificial intelligence, and specifically ma...