AIMC Topic: Age Factors

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Predicting atrial fibrillation in primary care using machine learning.

PloS one Nov 1, 2019
BACKGROUND: Atrial fibrillation (AF) is the most common sustained heart arrhythmia. However, as many cases are asymptomatic, a large proportion of patients remain undiagnosed until serious complications arise. Efficient, cost-effective detection of t...
Risk Assessment Antihypertensive Agents Humans Atrial Fibrillation Primary Health Care Neural Networks, Computer Body Mass Index Risk Factors Machine Learning Age Factors Retrospective Studies Aged Blood Pressure Female Adult Male Cardiovascular Diseases Middle Aged
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Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics.

NeuroImage Oct 11, 2019
There is significant interest in the development and application of deep neural networks (DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their classical counterparts in a variety of neuroimaging applications, yet there...
Datasets as Topic Connectome Neural Networks, Computer Intelligence Biological Specimen Banks Machine Learning Sex Factors Humans Brain Psychomotor Performance Female Image Interpretation, Computer-Assisted Aged Adult Young Adult Male Middle Aged Deep Learning Age Factors Magnetic Resonance Imaging
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Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis.

Human brain mapping Oct 1, 2019
Previous structural and functional neuroimaging studies have implicated distributed brain regions and networks in depression. However, there are no robust imaging biomarkers that are specific to depression, which may be due to clinical heterogeneity ...
Humans Machine Learning Female Adult Age Factors Male Magnetic Resonance Imaging Middle Aged Multimodal Imaging Anxiety Sex Factors Case-Control Studies Neuroimaging Functional Neuroimaging Depressive Disorder Depression
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A deep learning model for pediatric patient risk stratification.

The American journal of managed care Oct 1, 2019
OBJECTIVES: Current models for patient risk prediction rely on practitioner expertise and domain knowledge. This study presents a deep learning model-a type of machine learning that does not require human inputs-to analyze complex clinical and financ...
Humans Neural Networks, Computer Prospective Studies Reproducibility of Results Risk Factors Residence Characteristics Age Factors Health Services Sex Factors Accountable Care Organizations Health Resources Risk Assessment Deep Learning Child Socioeconomic Factors
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An Individualized Prediction Model for Long-term Lung Function Trajectory and Risk of COPD in the General Population.

Chest Sep 19, 2019
BACKGROUND: Prediction of future lung function will enable the identification of individuals at high risk of developing COPD, but the trajectory of lung function decline varies greatly among individuals. This study involved the development and valida...
Alkaline Phosphatase Hematocrit Dyspnea Sex Factors Body Height Alcohol Drinking Longitudinal Studies Age Factors Cough Forced Expiratory Volume Cigarette Smoking Serum Globulins Spirometry Triglycerides Serum Albumin Leukocyte Count Vital Capacity Bronchodilator Agents Algorithms Female Adult Pulmonary Disease, Chronic Obstructive Male Aging Middle Aged Risk Assessment Lung Cohort Studies Electrocardiography Humans Machine Learning
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A comprehensive knowledge base of synaptic electrophysiology in the rodent hippocampal formation.

Hippocampus Aug 31, 2019
The cellular and synaptic architecture of the rodent hippocampus has been described in thousands of peer-reviewed publications. However, no human- or machine-readable public catalog of synaptic electrophysiology data exists for this or any other neur...
Hippocampus Electrophysiological Phenomena Rodentia Male Age Factors Neuronal Plasticity Knowledge Bases Data Mining Synapses Animals
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Investigation of bias in an epilepsy machine learning algorithm trained on physician notes.

Epilepsia Aug 23, 2019
Racial disparities in the utilization of epilepsy surgery are well documented, but it is unknown whether a natural language processing (NLP) algorithm trained on physician notes would produce biased recommendations for epilepsy presurgical evaluation...
Humans Machine Learning Algorithms Healthcare Disparities Young Adult Child, Preschool Patient Selection Adult Child Referral and Consultation Middle Aged Age Factors Prejudice Infant Electroencephalography Adolescent Epilepsy
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Construct validation of machine learning in the prediction of short-term postoperative complications following total shoulder arthroplasty.

Journal of shoulder and elbow surgery Aug 3, 2019
BACKGROUND: We aimed to demonstrate that supervised machine learning (ML) models can better predict postoperative complications after total shoulder arthroplasty (TSA) than comorbidity indices.
Smoking Reoperation Serum Albumin Databases, Factual Arthroplasty, Replacement, Shoulder Female Operative Time Aged Predictive Value of Tests Male Supervised Machine Learning Middle Aged Hematocrit Postoperative Complications Patient Readmission Comorbidity Length of Stay ROC Curve Body Mass Index Humans Age Factors Forecasting Blood Transfusion
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Automated lesion segmentation with BIANCA: Impact of population-level features, classification algorithm and locally adaptive thresholding.

NeuroImage Jul 31, 2019
White matter hyperintensities (WMH) or white matter lesions exhibit high variability in their characteristics both at population- and subject-level, making their detection a challenging task. Population-level factors such as age, vascular risk factor...
Male Pattern Recognition, Automated Aging Brain Diseases Middle Aged Humans Neuroimaging Age Factors Machine Learning White Matter Magnetic Resonance Imaging Female Image Interpretation, Computer-Assisted Aged Aged, 80 and over
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Artificial neural networks reveal individual differences in metacognitive monitoring of memory.

PloS one Jul 31, 2019
Previous work supports an age-specific impairment for recognition memory of pairs of words and other stimuli. The present study tested the generalization of an associative deficit across word, name, and nonword stimulus types in younger and older adu...
Age Factors Memory Disorders Individuality Memory Recognition, Psychology Association Learning Aged, 80 and over Young Adult Adult Humans Metacognition Middle Aged Neural Networks, Computer Adolescent Female Aged
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