AIMC Topic: Machine Learning

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Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants.

PloS one May 15, 2019
BACKGROUND: Identifying people at risk of cardiovascular diseases (CVD) is a cornerstone of preventative cardiology. Risk prediction models currently recommended by clinical guidelines are typically based on a limited number of predictors with sub-op...
Proportional Hazards Models Risk Assessment Population Surveillance Prospective Studies Risk Factors Prognosis Biological Specimen Banks Male Female United Kingdom Cardiovascular Diseases Reproducibility of Results Humans Machine Learning Algorithms
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Semantic Face Hallucination: Super-Resolving Very Low-Resolution Face Images with Supplementary Attributes.

IEEE transactions on pattern analysis and machine intelligence May 14, 2019
Given a tiny face image, existing face hallucination methods aim at super-resolving its high-resolution (HR) counterpart by learning a mapping from an exemplary dataset. Since a low-resolution (LR) input patch may correspond to many HR candidate patc...
Neural Networks, Computer Machine Learning Algorithms Image Processing, Computer-Assisted Semantics Face Humans
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Machine-learning identifies Parkinson's disease patients based on resting-state between-network functional connectivity.

The British journal of radiology May 14, 2019
OBJECTIVE: Evaluation of a data-driven, model-based classification approach to discriminate idiopathic Parkinson's disease (PD) patients from healthy controls (HC) based on between-network connectivity in whole-brain resting-state functional MRI (rs-...
Humans Machine Learning Brain Middle Aged Magnetic Resonance Imaging Parkinson Disease Image Interpretation, Computer-Assisted Female Reproducibility of Results Sensitivity and Specificity Male
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A comparison of machine learning algorithms and covariate balance measures for propensity score matching and weighting.

Biometrical journal. Biometrische Zeitschrift May 14, 2019
Propensity score matching (PSM) and propensity score weighting (PSW) are popular tools to estimate causal effects in observational studies. We address two open issues: how to estimate propensity scores and assess covariate balance. Using simulations,...
Cesarean Section Observational Studies as Topic Labor, Induced Multivariate Analysis Machine Learning Pregnancy Female Propensity Score Monte Carlo Method Biometry Humans
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Predictive risk mapping of human leptospirosis using support vector machine classification and multilayer perceptron neural network.

Geospatial health May 14, 2019
Leptospirosis is a zoonotic disease found wherever human is in direct or indirect contact with contaminated water and environment. Considering the increasing number of cases of this disease in the northern part of Iran, identifying areas characterize...
Leptospirosis Humans Spatial Analysis Support Vector Machine Machine Learning Environment Models, Statistical Risk Factors Iran Incidence
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Machine learning to refine decision making within a syndromic surveillance service.

BMC public health May 14, 2019
BACKGROUND: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical al...
Machine Learning Algorithms Risk Assessment Public Health Humans Sentinel Surveillance England Decision Making Bayes Theorem
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A machine learning-based approach for predicting the outbreak of cardiovascular diseases in patients on dialysis.

Computer methods and programs in biomedicine May 13, 2019
BACKGROUND AND OBJECTIVE: Patients with End- Stage Kidney Disease (ESKD) have a unique cardiovascular risk. This study aims at predicting, with a certain precision, death and cardiovascular diseases in dialysis patients.
Registries Algorithms Bayes Theorem False Positive Reactions Databases, Factual Kidney Failure, Chronic Risk Cardiovascular Diseases Humans Biomarkers Italy Female Prognosis Middle Aged Aged Machine Learning Support Vector Machine Sensitivity and Specificity Models, Statistical Male
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A machine learning approach for predicting urine output after fluid administration.

Computer methods and programs in biomedicine May 13, 2019
BACKGROUND AND OBJECTIVE: To develop a machine learning model to predict urine output (UO) in sepsis patients after fluid resuscitation.
Machine Learning Algorithms Intensive Care Units Electronic Health Records Female Fluid Therapy Risk Factors Sepsis Critical Care Decision Support Systems, Clinical Aged Urination Kidney Function Tests Humans Sensitivity and Specificity Resuscitation Area Under Curve Male Middle Aged
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Label-Free Identification of White Blood Cells Using Machine Learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology May 13, 2019
White blood cell (WBC) differential counting is an established clinical routine to assess patient immune system status. Fluorescent markers and a flow cytometer are required for the current state-of-the-art method for determining WBC differential cou...
Leukocyte Count Flow Cytometry Leukocytes Quality Control Humans Machine Learning Algorithms
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Emotion Recognition from Multiband EEG Signals Using CapsNet.

Sensors (Basel, Switzerland) May 13, 2019
Emotion recognition based on multi-channel electroencephalograph (EEG) signals is becoming increasingly attractive. However, the conventional methods ignore the spatial characteristics of EEG signals, which also contain salient information related to...
Electroencephalography Signal Processing, Computer-Assisted Humans Entropy Electrodes Machine Learning Cerebral Cortex Emotions
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