AIMC Topic:
Databases, Factual

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A novel integrated action crossing method for drug-drug interaction prediction in non-communicable diseases.

Computer methods and programs in biomedicine Jun 22, 2018
BACKGROUND AND OBJECTIVE: Drug-drug interaction (DDI) is one of the main causes of toxicity and treatment inefficacy. This work focuses on non-communicable diseases (NCDs), the non-transmissible and long-lasting diseases since they are the leading ca...
Reproducibility of Results Support Vector Machine Cluster Analysis Area Under Curve Algorithms Humans Simvastatin Databases, Factual Neural Networks, Computer Noncommunicable Diseases False Positive Reactions Computer Simulation Machine Learning Quantitative Structure-Activity Relationship Drug Interactions Probability Cytochrome P-450 Enzyme System
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A study of generalizability of recurrent neural network-based predictive models for heart failure onset risk using a large and heterogeneous EHR data set.

Journal of biomedical informatics Jun 15, 2018
Recently, recurrent neural networks (RNNs) have been applied in predicting disease onset risks with Electronic Health Record (EHR) data. While these models demonstrated promising results on relatively small data sets, the generalizability and transfe...
Deep Learning Logistic Models Area Under Curve Heart Failure Aged, 80 and over Male Middle Aged Case-Control Studies Medical Informatics Neural Networks, Computer Algorithms Databases, Factual Computer Simulation Electronic Health Records Female Reproducibility of Results Aged Humans
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Predicting Survival From Large Echocardiography and Electronic Health Record Datasets: Optimization With Machine Learning.

JACC. Cardiovascular imaging Jun 13, 2018
OBJECTIVES: The goal of this study was to use machine learning to more accurately predict survival after echocardiography.
Predictive Value of Tests Data Mining Humans Heart Diseases Machine Learning Databases, Factual Prognosis Retrospective Studies Electronic Health Records Echocardiography Reproducibility of Results Risk Assessment Risk Factors Time Factors
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Fine-Tuning CNN Image Retrieval with No Human Annotation.

IEEE transactions on pattern analysis and machine intelligence Jun 12, 2018
Image descriptors based on activations of Convolutional Neural Networks (CNNs) have become dominant in image retrieval due to their discriminative power, compactness of representation, and search efficiency. Training of CNNs, either from scratch or f...
Databases, Factual Imaging, Three-Dimensional Image Processing, Computer-Assisted Humans Pattern Recognition, Automated Neural Networks, Computer
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Automatic hand phantom map generation and detection using decomposition support vector machines.

Biomedical engineering online Jun 11, 2018
BACKGROUND: There is a need for providing sensory feedback for myoelectric prosthesis users. Providing tactile feedback can improve object manipulation abilities, enhance the perceptual embodiment of myoelectric prostheses and help reduce phantom lim...
Fuzzy Logic Hand Automation Phantoms, Imaging Humans Databases, Factual Support Vector Machine
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Next-Generation Machine Learning for Biological Networks.

Cell Jun 7, 2018
Machine learning, a collection of data-analytical techniques aimed at building predictive models from multi-dimensional datasets, is becoming integral to modern biological research. By enabling one to generate models that learn from large datasets an...
Microbiota Algorithms Drug-Related Side Effects and Adverse Reactions Humans Databases, Factual Neural Networks, Computer Drug Discovery Machine Learning Computational Biology
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Predictive modeling of treatment resistant depression using data from STAR*D and an independent clinical study.

PloS one Jun 7, 2018
Identification of risk factors of treatment resistance may be useful to guide treatment selection, avoid inefficient trial-and-error, and improve major depressive disorder (MDD) care. We extended the work in predictive modeling of treatment resistant...
Depressive Disorder, Major Predictive Value of Tests Female Humans Drug Resistance Models, Biological Risk Factors Machine Learning Antidepressive Agents Adult Databases, Factual Male
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Unsupervised Bayesian Inference to Fuse Biosignal Sensory Estimates for Personalizing Care.

IEEE journal of biomedical and health informatics Jun 5, 2018
The role of sensing technologies, such as wearables, in delivering precision care is becoming widely acceptable. Given the very large quantities of sensor data that rapidly accumulate, there is a need to employ automated algorithms to label biosignal...
Male Middle Aged Infant Adolescent Child, Preschool Child Models, Statistical Unsupervised Machine Learning Female Aged Humans Young Adult Adult Algorithms Bayes Theorem Databases, Factual Medical Informatics Precision Medicine
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Benchmarking deep learning models on large healthcare datasets.

Journal of biomedical informatics Jun 5, 2018
Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications. However, few works exist w...
Databases, Factual Intensive Care Units Female Aged Humans Neural Networks, Computer Algorithms Forecasting Length of Stay Aged, 80 and over Hospital Mortality Male Benchmarking Middle Aged International Classification of Diseases Deep Learning
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A novel application of deep learning for single-lead ECG classification.

Computers in biology and medicine Jun 4, 2018
Detecting and classifying cardiac arrhythmias is critical to the diagnosis of patients with cardiac abnormalities. In this paper, a novel approach based on deep learning methodology is proposed for the classification of single-lead electrocardiogram ...
Humans Deep Learning Databases, Factual Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac
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