AI Medical Compendium Topic

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A Deep Transfer Learning Approach to Reducing the Effect of Electrode Shift in EMG Pattern Recognition-Based Control.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
An important barrier to commercialization of pattern recognition myoelectric control of prostheses is the lack of robustness to confounding factors such as electrode shift, skin impedance variations, and learning effects. To overcome this challenge, ...

Decoding and mapping task states of the human brain via deep learning.

Human brain mapping
Support vector machine (SVM)-based multivariate pattern analysis (MVPA) has delivered promising performance in decoding specific task states based on functional magnetic resonance imaging (fMRI) of the human brain. Conventionally, the SVM-MVPA requir...

3D-Convolutional Neural Network with Generative Adversarial Network and Autoencoder for Robust Anomaly Detection in Video Surveillance.

International journal of neural systems
As the surveillance devices proliferate, various machine learning approaches for video anomaly detection have been attempted. We propose a hybrid deep learning model composed of a video feature extractor trained by generative adversarial network with...

Adaptive transfer learning for EEG motor imagery classification with deep Convolutional Neural Network.

Neural networks : the official journal of the International Neural Network Society
In recent years, deep learning has emerged as a powerful tool for developing Brain-Computer Interface (BCI) systems. However, for deep learning models trained entirely on the data from a specific individual, the performance increase has only been mar...

A pre-training and self-training approach for biomedical named entity recognition.

PloS one
Named entity recognition (NER) is a key component of many scientific literature mining tasks, such as information retrieval, information extraction, and question answering; however, many modern approaches require large amounts of labeled training dat...

Neural state space alignment for magnitude generalization in humans and recurrent networks.

Neuron
A prerequisite for intelligent behavior is to understand how stimuli are related and to generalize this knowledge across contexts. Generalization can be challenging when relational patterns are shared across contexts but exist on different physical s...

Deep Learning for Multigrade Brain Tumor Classification in Smart Healthcare Systems: A Prospective Survey.

IEEE transactions on neural networks and learning systems
Brain tumor is one of the most dangerous cancers in people of all ages, and its grade recognition is a challenging problem for radiologists in health monitoring and automated diagnosis. Recently, numerous methods based on deep learning have been pres...

A cell-to-patient machine learning transfer approach uncovers novel basal-like breast cancer prognostic markers amongst alternative splice variants.

BMC biology
BACKGROUND: Breast cancer is amongst the 10 first causes of death in women worldwide. Around 20% of patients are misdiagnosed leading to early metastasis, resistance to treatment and relapse. Many clinical and gene expression profiles have been succe...

Medical-VLBERT: Medical Visual Language BERT for COVID-19 CT Report Generation With Alternate Learning.

IEEE transactions on neural networks and learning systems
Medical imaging technologies, including computed tomography (CT) or chest X-Ray (CXR), are largely employed to facilitate the diagnosis of the COVID-19. Since manual report writing is usually too time-consuming, a more intelligent auxiliary medical s...

Transfer learning for the generalization of artificial intelligence in breast cancer detection: a case-control study.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Some researchers have questioned whether artificial intelligence (AI) systems maintain their performance when used for women from populations not considered during the development of the system.