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Databases, Factual
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NiftyNet: a deep-learning platform for medical imaging.
Computer methods and programs in biomedicine
Jan 31, 2018
BACKGROUND AND OBJECTIVES: Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functional...
Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods.
Neural networks : the official journal of the International Neural Network Society
Jan 31, 2018
This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises Con...
A novel type of activation function in artificial neural networks: Trained activation function.
Neural networks : the official journal of the International Neural Network Society
Jan 31, 2018
Determining optimal activation function in artificial neural networks is an important issue because it is directly linked with obtained success rates. But, unfortunately, there is not any way to determine them analytically, optimal activation functio...
Spatial-Temporal Recurrent Neural Network for Emotion Recognition.
IEEE transactions on cybernetics
Jan 30, 2018
In this paper, we propose a novel deep learning framework, called spatial-temporal recurrent neural network (STRNN), to integrate the feature learning from both spatial and temporal information of signal sources into a unified spatial-temporal depend...
Analysis of Spatio-Temporal Representations for Robust Footstep Recognition with Deep Residual Neural Networks.
IEEE transactions on pattern analysis and machine intelligence
Jan 30, 2018
Human footsteps can provide a unique behavioural pattern for robust biometric systems. We propose spatio-temporal footstep representations from floor-only sensor data in advanced computational models for automatic biometric verification. Our models d...
Natural Language-based Machine Learning Models for the Annotation of Clinical Radiology Reports.
Radiology
Jan 30, 2018
Purpose To compare different methods for generating features from radiology reports and to develop a method to automatically identify findings in these reports. Materials and Methods In this study, 96 303 head computed tomography (CT) reports were ob...
Machine learning to parse breast pathology reports in Chinese.
Breast cancer research and treatment
Jan 29, 2018
INTRODUCTION: Large structured databases of pathology findings are valuable in deriving new clinical insights. However, they are labor intensive to create and generally require manual annotation. There has been some work in the bioinformatics communi...
Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU.
BMJ open
Jan 26, 2018
OBJECTIVES: We validate a machine learning-based sepsis-prediction algorithm () for the detection and prediction of three sepsis-related gold standards, using only six vital signs. We evaluate robustness to missing data, customisation to site-specifi...
Algorithms
Databases, Factual
Prognosis
Retrospective Studies
Humans
Machine Learning
San Francisco
Boston
Patients' Rooms
Area Under Curve
Emergency Service, Hospital
Vital Signs
Severity of Illness Index
Length of Stay
Sepsis
Adolescent
Hospital Mortality
ROC Curve
Shock, Septic
Young Adult
Adult
Intensive Care Units
Male
Female
Middle Aged
Aged
Viscosity Prediction in a Physiologically Controlled Ventricular Assist Device.
IEEE transactions on bio-medical engineering
Jan 24, 2018
OBJECTIVE: We present a novel machine learning model to accurately predict the blood-analog viscosity during support of a pathological circulation with a rotary ventricular assist device (VAD). The aim is the continuous monitoring of the hematocrit (...
Quantitative approaches to energy and glucose homeostasis: machine learning and modelling for precision understanding and prediction.
Journal of the Royal Society, Interface
Jan 24, 2018
Obesity is a major global public health problem. Understanding how energy homeostasis is regulated, and can become dysregulated, is crucial for developing new treatments for obesity. Detailed recording of individual behaviour and new imaging modaliti...
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