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Preoperative Prediction of Value Metrics and a Patient-Specific Payment Model for Primary Total Hip Arthroplasty: Development and Validation of a Deep Learning Model.
The Journal of arthroplasty
May 2, 2019
BACKGROUND: The primary objective was to develop and test an artificial neural network (ANN) that learns and predicts length of stay (LOS), inpatient charges, and discharge disposition for total hip arthroplasty. The secondary objective was to create...
Use of machine learning techniques in the development and refinement of a predictive model for early diagnosis of ankylosing spondylitis.
Clinical rheumatology
May 1, 2019
OBJECTIVE: To develop a predictive mathematical model for the early identification of ankylosing spondylitis (AS) based on the medical and pharmacy claims history of patients with and without AS.
An adverse drug effect mentions extraction method based on weighted online recurrent extreme learning machine.
Computer methods and programs in biomedicine
Apr 30, 2019
BACKGROUND AND OBJECTIVE: Automatic extraction of adverse drug effect (ADE) mentions from biomedical texts is a challenging research problem that has attracted significant attention from the pharmacovigilance and biomedical text mining communities. I...
Automated semantic labeling of pediatric musculoskeletal radiographs using deep learning.
Pediatric radiology
Apr 30, 2019
BACKGROUND: An automated method for identifying the anatomical region of an image independent of metadata labels could improve radiologist workflow (e.g., automated hanging protocols) and help facilitate the automated curation of large medical imagin...
Deep Learning for Diagnosis of Chronic Myocardial Infarction on Nonenhanced Cardiac Cine MRI.
Radiology
Apr 30, 2019
Background Renal impairment is common in patients with coronary artery disease and, if severe, late gadolinium enhancement (LGE) imaging for myocardial infarction (MI) evaluation cannot be performed. Purpose To develop a fully automatic framework for...
Analysis of Unstructured Text-Based Data Using Machine Learning Techniques: The Case of Pediatric Emergency Department Records in Nicaragua.
Medical care research and review : MCRR
Apr 29, 2019
Free-text information is still widely used in emergency department (ED) records. Machine learning techniques are useful for analyzing narratives, but they have been used mostly for English-language data sets. Considering such a framework, the perform...
Transfer Learning for Brain-Computer Interfaces: A Euclidean Space Data Alignment Approach.
IEEE transactions on bio-medical engineering
Apr 29, 2019
OBJECTIVE: This paper targets a major challenge in developing practical electroencephalogram (EEG)-based brain-computer interfaces (BCIs): how to cope with individual differences so that better learning performance can be obtained for a new subject, ...
Assessing cognitive mental workload via EEG signals and an ensemble deep learning classifier based on denoising autoencoders.
Computers in biology and medicine
Apr 29, 2019
To estimate the reliability and cognitive states of operator performance in a human-machine collaborative environment, we propose a novel human mental workload (MW) recognizer based on deep learning principles and utilizing the features of the electr...
Assessment of Electrocardiogram Rhythms by GoogLeNet Deep Neural Network Architecture.
Journal of healthcare engineering
Apr 28, 2019
The aim of this study is to design GoogLeNet deep neural network architecture by expanding the kernel size of the inception layer and combining the convolution layers to classify the electrocardiogram (ECG) beats into a normal sinus rhythm, premature...
JointRCNN: A Region-Based Convolutional Neural Network for Optic Disc and Cup Segmentation.
IEEE transactions on bio-medical engineering
Apr 25, 2019
OBJECTIVE: The purpose of this paper is to propose a novel algorithm for joint optic disc and cup segmentation, which aids the glaucoma detection.
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