Humans

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Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES.

Environmental health : a global access science source Sep 26, 2017
BACKGROUND: There is growing concern of health effects of exposure to pollutant mixtures. We initially proposed an Environmental Risk Score (ERS) as a summary measure to examine the risk of exposure to multi-pollutants in epidemiologic research consi...
Linear Models Middle Aged Risk Assessment Prevalence United States Environmental Pollutants Oxidative Stress Metals Adult Male Cardiovascular Diseases Female Aged Young Adult Humans Machine Learning
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Anticipatory detection of turning in humans for intuitive control of robotic mobility assistance.

Bioinspiration & biomimetics Sep 26, 2017
Many wearable lower-limb robots for walking assistance have been developed in recent years. However, it remains unclear how they can be commanded in an intuitive and efficient way by their user. In particular, providing robotic assistance to neurolog...
Robotics Pelvis Walking Prosthesis Design Humans Biomechanical Phenomena Orthotic Devices Torso Orientation Head Task Performance and Analysis Locomotion
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Distant Supervision with Transductive Learning for Adverse Drug Reaction Identification from Electronic Medical Records.

Journal of healthcare engineering Sep 26, 2017
Information extraction and knowledge discovery regarding adverse drug reaction (ADR) from large-scale clinical texts are very useful and needy processes. Two major difficulties of this task are the lack of domain experts for labeling examples and int...
Supervised Machine Learning Drug-Related Side Effects and Adverse Reactions Knowledge Bases Electronic Health Records Language Natural Language Processing Pattern Recognition, Automated Adverse Drug Reaction Reporting Systems Software Information Storage and Retrieval Algorithms Medical Informatics Humans Linear Models
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Meaningless comparisons lead to false optimism in medical machine learning.

PloS one Sep 26, 2017
A new trend in medicine is the use of algorithms to analyze big datasets, e.g. using everything your phone measures about you for diagnostics or monitoring. However, these algorithms are commonly compared against weak baselines, which may contribute ...
Humans Machine Learning Algorithms Mood Disorders
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Localization of Origins of Premature Ventricular Contraction by Means of Convolutional Neural Network From 12-Lead ECG.

IEEE transactions on bio-medical engineering Sep 25, 2017
OBJECTIVE: This paper proposes a novel method to localize origins of premature ventricular contractions (PVCs) from 12-lead electrocardiography (ECG) using convolutional neural network (CNN) and a realistic computer heart model.
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Male Middle Aged Electrocardiography Algorithms Signal Processing, Computer-Assisted Humans Female Ventricular Premature Complexes Neural Networks, Computer Aged Adult
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Prediction of lung cancer patient survival via supervised machine learning classification techniques.

International journal of medical informatics Sep 25, 2017
Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large datasets such as the Surveillance, Epidemiology, and End Results (SEER) program database. In particular for lung cancer, it is not we...
Lung Neoplasms Support Vector Machine Machine Learning Databases, Factual Survival Rate Humans
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Relating dynamic brain states to dynamic machine states: Human and machine solutions to the speech recognition problem.

PLoS computational biology Sep 25, 2017
There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiologic...
Neural Networks, Computer Brain Female Young Adult Humans Electroencephalography Speech Recognition Software Speech Perception Magnetoencephalography Adult Male Models, Neurological
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Serum levels of chemical elements in esophageal squamous cell carcinoma in Anyang, China: a case-control study based on machine learning methods.

BMJ open Sep 24, 2017
OBJECTIVES: Esophageal squamous cell carcinoma (ESCC) is the predominant form of esophageal carcinoma with extremely aggressive nature and low survival rate. The risk factors for ESCC in the high-incidence areas of China remain unclear. We used machi...
Humans Esophageal Neoplasms Esophageal Squamous Cell Carcinoma Biomarkers, Tumor Male Middle Aged Zinc Copper Carcinoma, Squamous Cell Machine Learning Case-Control Studies Reproducibility of Results Retrospective Studies Risk Factors Female Selenium
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Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies.

Computational and mathematical methods in medicine Sep 24, 2017
Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Sev...
Case-Control Studies Algorithms Patient Selection Research Design Selection Bias Hepatitis Computer Simulation Humans Machine Learning Software
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If your hospital has RATS, do not exterminate.

The Journal of thoracic and cardiovascular surgery Sep 23, 2017
Humans Carcinoma, Non-Small-Cell Lung Robotics Hospitals Lung Neoplasms Robotic Surgical Procedures
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