AIMC Topic:
Predictive Value of Tests
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Prediction of central neuropathic pain in spinal cord injury based on EEG classifier.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
May 23, 2018
OBJECTIVES: To create a classifier based on electroencephalography (EEG) to identify spinal cord injured (SCI) participants at risk of developing central neuropathic pain (CNP) by comparing them with patients who had already developed pain and with a...
Machine learning in the integration of simple variables for identifying patients with myocardial ischemia.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
May 22, 2018
BACKGROUND: A significant number of variables are obtained when characterizing patients suspected with myocardial ischemia or at risk of MACE. Guidelines typically use a handful of them to support further workup or therapeutic decisions. However, it ...
High-Grade Serous Ovarian Cancer: Use of Machine Learning to Predict Abdominopelvic Recurrence on CT on the Basis of Serial Cancer Antigen 125 Levels.
Journal of the American College of Radiology : JACR
May 19, 2018
PURPOSE: The aim of this study was to use machine learning to predict abdominal recurrence on CT on the basis of serial cancer antigen 125 (CA125) levels in patients with advanced high-grade serous ovarian cancer on surveillance.
Screening for active pulmonary tuberculosis: Development and applicability of artificial neural network models.
Tuberculosis (Edinburgh, Scotland)
May 19, 2018
Tuberculosis (TB) remains a significant public health challenge, motivated by the diversity of healthcare epidemiological settings, as other factors. Cost-effective screening has substantial importance for TB control, demanding new diagnostic tools. ...
Neural Networks, Computer
Decision Support Techniques
Databases, Factual
Tuberculosis, Pulmonary
Female
Risk Assessment
Mycobacterium tuberculosis
Reproducibility of Results
Risk Factors
Brazil
Bacteriological Techniques
Young Adult
Lung
Humans
Decision Support Systems, Clinical
Adult
Prevalence
Mass Screening
Male
Diagnosis, Computer-Assisted
Predictive Value of Tests
Middle Aged
Sputum
A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals.
Computers in biology and medicine
May 17, 2018
The electroencephalogram (EEG) is the most prominent means to study epilepsy and capture changes in electrical brain activity that could declare an imminent seizure. In this work, Long Short-Term Memory (LSTM) networks are introduced in epileptic sei...
A Novel Deep Learning Approach for Automated Diagnosis of Acute Ischemic Infarction on Computed Tomography.
JACC. Cardiovascular imaging
May 16, 2018
Research on Improved Depth Belief Network-Based Prediction of Cardiovascular Diseases.
Journal of healthcare engineering
May 9, 2018
Quantitative analysis and prediction can help to reduce the risk of cardiovascular disease. Quantitative prediction based on traditional model has low accuracy. The variance of model prediction based on shallow neural network is larger. In this paper...
Identifying β-thalassemia carriers using a data mining approach: The case of the Gaza Strip, Palestine.
Artificial intelligence in medicine
May 3, 2018
Thalassemia is considered one of the most common genetic blood disorders that has received excessive attention in the medical research fields worldwide. Under this context, one of the greatest challenges for healthcare professionals is to correctly d...
Lung sounds classification using convolutional neural networks.
Artificial intelligence in medicine
May 1, 2018
Lung sounds convey relevant information related to pulmonary disorders, and to evaluate patients with pulmonary conditions, the physician or the doctor uses the traditional auscultation technique. However, this technique suffers from limitations. For...
Male
Middle Aged
Lung
Deep Learning
Humans
Adolescent
Prognosis
Acoustics
Infant, Newborn
Child
Female
Sound Spectrography
Reproducibility of Results
Support Vector Machine
Pattern Recognition, Automated
Aged
Predictive Value of Tests
Auscultation
Adult
Signal Processing, Computer-Assisted
Respiratory Sounds
Lung Diseases
Machine learning in cardiac CT: Basic concepts and contemporary data.
Journal of cardiovascular computed tomography
Apr 30, 2018
Propelled by the synergy of the groundbreaking advancements in the ability to analyze high-dimensional datasets and the increasing availability of imaging and clinical data, machine learning (ML) is poised to transform the practice of cardiovascular ...
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