AIMC Topic: Pattern Recognition, Automated
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Early Expression Detection via Online Multi-Instance Learning With Nonlinear Extension.
IEEE transactions on neural networks and learning systems
Oct 3, 2018
Video-based facial expression recognition has received substantial attention over the past decade, while early expression detection (EED) is still a relatively new and challenging problem. The goal of EED is to identify an expression as quickly as po...
Hypergraph-Induced Convolutional Networks for Visual Classification.
IEEE transactions on neural networks and learning systems
Oct 2, 2018
At present, convolutional neural networks (CNNs) have become popular in visual classification tasks because of their superior performance. However, CNN-based methods do not consider the correlation of visual data to be classified. Recently, graph con...
Towards automated clinical coding.
International journal of medical informatics
Oct 2, 2018
BACKGROUND: Patients' encounters with healthcare services must undergo clinical coding. These codes are typically derived from free-text notes. Manual clinical coding is expensive, time-consuming and prone to error. Automated clinical coding systems ...
An SVM approach for identifying atrial fibrillation.
Physiological measurement
Sep 27, 2018
OBJECTIVES: We designed an automated algorithm to classify short electrocardiogram (ECG) strips into four categories: normal rhythm, atrial fibrillation, noisy segment, or other rhythm disturbances.
Multi-dimensional proprio-proximus machine learning for assessment of myocardial infarction.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Sep 26, 2018
This work presents a novel analysis methodology that utilises high-resolution, multi-dimensional information to better classify regions of the left ventricle after myocardial infarction. Specifically, the focus is to determine degree of infarction in...
Automatic glomerular identification and quantification of histological phenotypes using image analysis and machine learning.
American journal of physiology. Renal physiology
Sep 26, 2018
Current methods of scoring histological kidney samples, specifically glomeruli, do not allow for collection of quantitative data in a high-throughput and consistent manner. Neither untrained individuals nor computers are presently capable of identify...
Kidney Diseases
Predictive Value of Tests
Biopsy
Humans
Workflow
Machine Learning
Kidney Glomerulus
Mice, Transgenic
Microscopy
Rats
Female
Image Interpretation, Computer-Assisted
Disease Models, Animal
Reproducibility of Results
Pattern Recognition, Automated
Mice, Inbred C57BL
Animals
Species Specificity
Male
Software
Diagnosis, Computer-Assisted
Automation, Laboratory
Phenotype
Automatic Lacunae Localization in Placental Ultrasound Images via Layer Aggregation.
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Sep 26, 2018
Accurate localization of structural abnormalities is a precursor for image-based prenatal assessment of adverse conditions. For clinical screening and diagnosis of abnormally invasive placenta (AIP), a life-threatening obstetric condition, qualitativ...
ECG signal classification for the detection of cardiac arrhythmias using a convolutional recurrent neural network.
Physiological measurement
Sep 24, 2018
OBJECTIVE: The electrocardiogram (ECG) provides an effective, non-invasive approach for clinical diagnosis in patients with cardiac diseases such as atrial fibrillation (AF). AF is the most common cardiac rhythm disturbance and affects ~2% of the gen...
Application of identity vectors for EEG classification.
Journal of neuroscience methods
Sep 19, 2018
BACKGROUND: Finding an optimal EEG subject verification algorithm is a long standing goal within the EEG community. For every advancement made, another feature set, classifier, or dataset is often introduced; tracking improvements in classification w...
A Continuously Updated, Computationally Efficient Stress Recognition Framework Using Electroencephalogram (EEG) by Applying Online Multitask Learning Algorithms (OMTL).
IEEE journal of biomedical and health informatics
Sep 18, 2018
Recognizing the factors that cause stress is a crucial step toward early detection of stressors. In this regard, several studies make an effort to recognize individuals' stress using an Electroencephalogram (EEG). However, current EEG-based stress re...
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