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Databases, Factual
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Multi-Source Ensemble Learning for the Remote Prediction of Parkinson's Disease in the Presence of Source-Wise Missing Data.
IEEE transactions on bio-medical engineering
Nov 5, 2018
As the collection of mobile health data becomes pervasive, missing data can make large portions of datasets inaccessible for analysis. Missing data has shown particularly problematic for remotely diagnosing and monitoring Parkinson's disease (PD) usi...
A unified non-linear approach based on recurrence quantification analysis and approximate entropy: application to the classification of heart rate variability of age-stratified subjects.
Medical & biological engineering & computing
Nov 3, 2018
This paper presents a unified approach based on the recurrence quantification analysis (RQA) and approximate entropy (ApEn) for the classification of heart rate variability (HRV). In this paper, the optimum tolerance threshold (r) corresponding to Ap...
Exudate detection in fundus images using deeply-learnable features.
Computers in biology and medicine
Nov 3, 2018
Presence of exudates on a retina is an early sign of diabetic retinopathy, and automatic detection of these can improve the diagnosis of the disease. Convolutional Neural Networks (CNNs) have been used for automatic exudate detection, but with poor p...
Large-Scale Multi-Class Image-Based Cell Classification With Deep Learning.
IEEE journal of biomedical and health informatics
Oct 31, 2018
Recent advances in ultra-high-throughput microscopy have enabled a new generation of cell classification methodologies using image-based cell phenotypes alone. In contrast to current single-cell analysis techniques that rely solely on slow and costly...
Automatic localization of the subthalamic nucleus on patient-specific clinical MRI by incorporating 7 T MRI and machine learning: Application in deep brain stimulation.
Human brain mapping
Oct 31, 2018
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has shown clinical potential for relieving the motor symptoms of advanced Parkinson's disease. While accurate localization of the STN is critical for consistent across-patients effective D...
A novel approach to emotion recognition using local subset feature selection and modified Dempster-Shafer theory.
Behavioral and brain functions : BBF
Oct 31, 2018
BACKGROUND: Emotion recognition is an increasingly important field of research in brain computer interactions.
Toward analyzing and synthesizing previous research in early prediction of cardiac arrest using machine learning based on a multi-layered integrative framework.
Journal of biomedical informatics
Oct 30, 2018
BACKGROUND: One of the significant problems in the field of healthcare is the low survival rate of people who have experienced sudden cardiac arrest. Early prediction of cardiac arrest can provide the time required for intervening and preventing its ...
A Machine-Learning Approach for Detection and Quantification of QRS Fragmentation.
IEEE journal of biomedical and health informatics
Oct 29, 2018
OBJECTIVE: Fragmented QRS (fQRS) is an accessible biomarker and indication of myocardial scarring that can be detected from the electrocardiogram (ECG). Nowadays, fQRS scoring is done on a visual basis, which is time consuming and leads to subjective...
A systematic literature review and classification of knowledge discovery in traditional medicine.
Computer methods and programs in biomedicine
Oct 27, 2018
INTRODUCTION AND OBJECTIVE: Despite the importance of machine learning methods application in traditional medicine there is a no systematic literature review and a classification for this field. This is the first comprehensive literature review of th...
Medicine, Traditional
Diagnosis, Computer-Assisted
Persia
China
Medicine, Ayurvedic
India
Medicine, Chinese Traditional
Plant Preparations
Artificial Intelligence
Support Vector Machine
Bayes Theorem
Symptom Assessment
Japan
Machine Learning
Medicine, Kampo
Data Mining
Databases, Factual
Humans
Neural Networks, Computer
Delimiting the knowledge space and the design space of nanostructured lipid carriers through Artificial Intelligence tools.
International journal of pharmaceutics
Oct 26, 2018
Nanostructured lipid carriers (NLC) are biocompatible and biodegradable nanoscale systems with extensive application for controlled drug release. However, the development of optimal nanosystems along with a reproducible manufacturing process is still...
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