AIMC Topic: Neural Networks, Computer

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Utilizing dynamic treatment information for MACE prediction of acute coronary syndrome.

BMC medical informatics and decision making
BACKGROUND: Main adverse cardiac events (MACE) are essentially composite endpoints for assessing safety and efficacy of treatment processes of acute coronary syndrome (ACS) patients. Timely prediction of MACE is highly valuable for improving the effe...

NeuO: Exploiting the sentimental bias between ratings and reviews with neural networks.

Neural networks : the official journal of the International Neural Network Society
Traditional recommender systems rely on user profiling based on either user ratings or reviews through bi-sentimental analysis. However, in real-world scenarios, there are two common phenomena: (1) users only provide ratings for items but without det...

Validating Deep Neural Networks for Online Decoding of Motor Imagery Movements from EEG Signals.

Sensors (Basel, Switzerland)
Non-invasive, electroencephalography (EEG)-based brain-computer interfaces (BCIs) on motor imagery movements translate the subject's motor intention into control signals through classifying the EEG patterns caused by different imagination tasks, e.g....

A GIS-Based Artificial Neural Network Model for Spatial Distribution of Tuberculosis across the Continental United States.

International journal of environmental research and public health
Despite the usefulness of artificial neural networks (ANNs) in the study of various complex problems, ANNs have not been applied for modeling the geographic distribution of tuberculosis (TB) in the US. Likewise, ecological level researches on TB inci...

Automatic thyroid nodule recognition and diagnosis in ultrasound imaging with the YOLOv2 neural network.

World journal of surgical oncology
BACKGROUND: In this study, images of 2450 benign thyroid nodules and 2557 malignant thyroid nodules were collected and labeled, and an automatic image recognition and diagnosis system was established by deep learning using the YOLOv2 neural network. ...

An Intelligent Sleep Apnea Classification System Based on EEG Signals.

Journal of medical systems
Sleep Apnea is a sleep disorder which causes stop in breathing for a short duration of time that happens to human beings and animals during sleep. Electroencephalogram (EEG) plays a vital role in detecting the sleep apnea by sensing and recording the...

Nasopharyngeal carcinoma segmentation based on enhanced convolutional neural networks using multi-modal metric learning.

Physics in medicine and biology
Multi-modality examinations have been extensively applied in current clinical cancer management. Leveraging multi-modality medical images can be highly beneficial for automated tumor segmentation as they provide complementary information that could m...

An Ensemble Model With Clustering Assumption for Warfarin Dose Prediction in Chinese Patients.

IEEE journal of biomedical and health informatics
The prediction of daily stable warfarin dosage for a specific patient is difficult. To improve the predictive accuracy and to build a highly accurate predictive model, we developed an ensemble learning method, called evolutionary fuzzy c-mean (EFCM) ...

DCDE: An Efficient Deep Convolutional Divergence Encoding Method for Human Promoter Recognition.

IEEE transactions on nanobioscience
Efficient human promoter feature extraction is still a major challenge in genome analysis as it can better understand human gene regulation and will be useful for experimental guidance. Although many machine learning algorithms have been developed fo...