AIMC Topic: Algorithms

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Spatial-Frequency Feature Learning and Classification of Motor Imagery EEG Based on Deep Convolution Neural Network.

Computational and mathematical methods in medicine
EEG pattern recognition is an important part of motor imagery- (MI-) based brain computer interface (BCI) system. Traditional EEG pattern recognition algorithm usually includes two steps, namely, feature extraction and feature classification. In feat...

Time-distanced gates in long short-term memory networks.

Medical image analysis
The Long Short-Term Memory (LSTM) network is widely used in modeling sequential observations in fields ranging from natural language processing to medical imaging. The LSTM has shown promise for interpreting computed tomography (CT) in lung screening...

Discretely-constrained deep network for weakly supervised segmentation.

Neural networks : the official journal of the International Neural Network Society
An efficient strategy for weakly-supervised segmentation is to impose constraints or regularization priors on target regions. Recent efforts have focused on incorporating such constraints in the training of convolutional neural networks (CNN), howeve...

Landslide displacement interval prediction using lower upper bound estimation method with pre-trained random vector functional link network initialization.

Neural networks : the official journal of the International Neural Network Society
Interval prediction is an efficient approach to quantifying the uncertainties associated with landslide evolution. In this paper, a novel method, termed lower upper bound estimation (LUBE), of constructing prediction intervals (PIs) based on neural n...

Adversarial active learning for the identification of medical concepts and annotation inconsistency.

Journal of biomedical informatics
OBJECTIVE: Named entity recognition (NER) is a principal task in the biomedical field and deep learning-based algorithms have been widely applied to biomedical NER. However, all of these methods that are applied to biomedical corpora use only annotat...

Performance of a Machine Learning Algorithm in Predicting Outcomes of Aortic Valve Replacement.

The Annals of thoracic surgery
BACKGROUND: This study evaluated the performance of a machine learning (ML) algorithm in predicting outcomes of surgical aortic valve replacement (SAVR).

Efficacy of intelligent diagnosis with a dynamic uncertain causality graph model for rare disorders of sex development.

Frontiers of medicine
Disorders of sex development (DSD) are a group of rare complex clinical syndromes with multiple etiologies. Distinguishing the various causes of DSD is quite difficult in clinical practice, even for senior general physicians because of the similar an...

Modeling of Cu(II) Adsorption from an Aqueous Solution Using an Artificial Neural Network (ANN).

Molecules (Basel, Switzerland)
This research optimized the adsorption performance of rice husk char (RHC4) for copper (Cu(II)) from an aqueous solution. Various physicochemical analyses such as Fourier transform infrared spectroscopy (FTIR), field-emission scanning electron micros...

Exploring supervised machine learning approaches to predicting Veterans Health Administration chiropractic service utilization.

Chiropractic & manual therapies
BACKGROUND: Chronic spinal pain conditions affect millions of US adults and carry a high healthcare cost burden, both direct and indirect. Conservative interventions for spinal pain conditions, including chiropractic care, have been associated with l...