AIMC Topic: Machine Learning

Clear Filters Showing 25541 to 25550 of 34417 articles

Using Dictionary Pair Learning for Seizure Detection.

International journal of neural systems
Automatic seizure detection is extremely important in the monitoring and diagnosis of epilepsy. The paper presents a novel method based on dictionary pair learning (DPL) for seizure detection in the long-term intracranial electroencephalogram (EEG) r...

Concatenated and Connected Random Forests With Multiscale Patch Driven Active Contour Model for Automated Brain Tumor Segmentation of MR Images.

IEEE transactions on medical imaging
Segmentation of brain tumors from magnetic resonance imaging (MRI) data sets is of great importance for improved diagnosis, growth rate prediction, and treatment planning. However, automating this process is challenging due to the presence of severe ...

Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: There are concerns over gadolinium deposition from gadolinium-based contrast agents (GBCA) administration.

Effective neural network training with adaptive learning rate based on training loss.

Neural networks : the official journal of the International Neural Network Society
A method that uses an adaptive learning rate is presented for training neural networks. Unlike most conventional updating methods in which the learning rate gradually decreases during training, the proposed method increases or decreases the learning ...

Salient object detection based on multi-scale contrast.

Neural networks : the official journal of the International Neural Network Society
Due to the development of deep learning networks, a salient object detection based on deep learning networks, which are used to extract the features, has made a great breakthrough compared to the traditional methods. At present, the salient object de...

Evaluating Report Text Variation and Informativeness: Natural Language Processing of CT Chest Imaging for Pulmonary Embolism.

Journal of the American College of Radiology : JACR
OBJECTIVE: The aim of this study was to quantify the variability of language in free text reports of pulmonary embolus (PE) studies and to gauge the informativeness of free text to predict PE diagnosis using machine learning as proxy for human unders...

Real-Time Human Detection for Aerial Captured Video Sequences via Deep Models.

Computational intelligence and neuroscience
Human detection in videos plays an important role in various real life applications. Most of traditional approaches depend on utilizing handcrafted features which are problem-dependent and optimal for specific tasks. Moreover, they are highly suscept...

A study of association of Oncotype DX recurrence score with DCE-MRI characteristics using multivariate machine learning models.

Journal of cancer research and clinical oncology
PURPOSE: To determine whether multivariate machine learning models of algorithmically assessed magnetic resonance imaging (MRI) features from breast cancer patients are associated with Oncotype DX (ODX) test recurrence scores.

A review of machine learning in obesity.

Obesity reviews : an official journal of the International Association for the Study of Obesity
Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine learning prov...

Automated detection of preserved photoreceptor on optical coherence tomography in choroideremia based on machine learning.

Journal of biophotonics
Optical coherence tomography (OCT) can demonstrate early deterioration of the photoreceptor integrity caused by inherited retinal degeneration diseases (IRDs). A machine learning method based on random forests was developed to automatically detect co...