AIMC Topic: Aged, 80 and over

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An automated machine learning approach to predict brain age from cortical anatomical measures.

Human brain mapping May 16, 2020
The use of machine learning (ML) algorithms has significantly increased in neuroscience. However, from the vast extent of possible ML algorithms, which one is the optimal model to predict the target variable? What are the hyperparameters for such a m...
Male Middle Aged Adolescent Image Processing, Computer-Assisted Models, Theoretical Age Factors Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Datasets as Topic Neuroimaging Female Aged Aged, 80 and over Young Adult Adult Cerebral Cortex Humans Machine Learning
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Predicting hospital admission for older emergency department patients: Insights from machine learning.

International journal of medical informatics May 16, 2020
BACKGROUND: Emergency departments (ED) are a portal of entry into the hospital and are uniquely positioned to influence the health care trajectories of older adults seeking medical attention. Older adults present to the ED with distinct needs and com...
Canada Emergency Service, Hospital Geriatric Assessment Humans Machine Learning Prospective Studies Female Hospitalization Aged Aged, 80 and over Male Risk Assessment ROC Curve
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Natural Language Processing Improves Detection of Nonsevere Hypoglycemia in Medical Records Versus Coding Alone in Patients With Type 2 Diabetes but Does Not Improve Prediction of Severe Hypoglycemia Events: An Analysis Using the Electronic Medical Record in a Large Health System.

Diabetes care May 15, 2020
OBJECTIVE: To determine if natural language processing (NLP) improves detection of nonsevere hypoglycemia (NSH) in patients with type 2 diabetes and no NSH documentation by diagnosis codes and to measure if NLP detection improves the prediction of fu...
Clinical Decision Rules Middle Aged Aged Severity of Illness Index Aged, 80 and over Diabetes Mellitus, Type 2 Humans Young Adult Natural Language Processing United States Algorithms Adult Hypoglycemia Predictive Value of Tests Electronic Health Records Male Information Storage and Retrieval Female International Classification of Diseases Community Health Planning
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Identifying drugs with disease-modifying potential in Parkinson's disease using artificial intelligence and pharmacoepidemiology.

Pharmacoepidemiology and drug safety May 14, 2020
PURPOSE: The aim of the study was to assess the feasibility of an approach combining computational methods and pharmacoepidemiology to identify potentially disease-modifying drugs in Parkinson's disease (PD).
Dexamethasone Antiparkinson Agents Pharmacoepidemiology Theophylline Insurance Claim Review Pentoxifylline Aged, 80 and over Male Case-Control Studies Ontario Parkinson Disease Humans Artificial Intelligence Female Aged
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Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study.

The Lancet. Digital health May 14, 2020
BACKGROUND: CT is the most common imaging modality in traumatic brain injury (TBI). However, its conventional use requires expert clinical interpretation and does not provide detailed quantitative outputs, which may have prognostic importance. We aim...
Reproducibility of Results Aged Aged, 80 and over Young Adult Adult Humans Brain Tomography, X-Ray Computed Female Brain Injuries, Traumatic Europe Radiographic Image Interpretation, Computer-Assisted Male Semantics Middle Aged Deep Learning Adolescent Child
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Automatic Triage of 12-Lead ECGs Using Deep Convolutional Neural Networks.

Journal of the American Heart Association May 14, 2020
BACKGROUND The correct interpretation of the ECG is pivotal for the accurate diagnosis of many cardiac abnormalities, and conventional computerized interpretation has not been able to reach physician-level accuracy in detecting (acute) cardiac abnorm...
Heart Diseases Automation Adolescent Electrocardiography Predictive Value of Tests Clinical Decision-Making Humans Triage Female Young Adult Signal Processing, Computer-Assisted Reproducibility of Results Adult Aged Male Aged, 80 and over Middle Aged Deep Learning
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Prediction of hypertension, hyperglycemia and dyslipidemia from retinal fundus photographs via deep learning: A cross-sectional study of chronic diseases in central China.

PloS one May 14, 2020
Retinal fundus photography provides a non-invasive approach for identifying early microcirculatory alterations of chronic diseases prior to the onset of overt clinical complications. Here, we developed neural network models to predict hypertension, h...
Deep Learning Chronic Disease Young Adult Humans China Female Fundus Oculi Adult ROC Curve Risk Factors Cross-Sectional Studies Models, Biological Hypertension Aged Male Retina Hyperglycemia Aged, 80 and over Middle Aged Dyslipidemias
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Rehabilitation of older people with Parkinson's disease: an innovative protocol for RCT study to evaluate the potential of robotic-based technologies.

BMC neurology May 13, 2020
BACKGROUND: Parkinson's disease is one of the most frequent causes of disability among the older adults. It is a chronic-progressive neuro-degenerative disease, characterized by several motor disorders. Balance disorders are a symptom that involves t...
Robotics Postural Balance Single-Blind Method Exercise Therapy Gait Disorders, Neurologic Aged, 80 and over Male Accidental Falls Parkinson Disease Randomized Controlled Trials as Topic Sensation Disorders Humans Research Design Female Aged
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Improvement of electrocardiographic diagnostic accuracy of left ventricular hypertrophy using a Machine Learning approach.

PloS one May 13, 2020
The electrocardiogram (ECG) is the most common tool used to predict left ventricular hypertrophy (LVH). However, it is limited by its low accuracy (<60%) and sensitivity (30%). We set forth the hypothesis that the Machine Learning (ML) C5.0 algorithm...
Adult Male Humans Middle Aged Machine Learning Electrocardiography Female Hypertrophy, Left Ventricular Aged Aged, 80 and over
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Usefulness of deep learning-assisted identification of hyperdense MCA sign in acute ischemic stroke: comparison with readers' performance.

Japanese journal of radiology May 12, 2020
PURPOSE: To evaluate the usefulness of deep learning-assisted diagnosis for identifying hyperdense middle cerebral artery sign (HMCAS) on non-contrast computed tomography in comparison with the diagnostic performance of neuroradiologists.
Humans Retrospective Studies Tomography, X-Ray Computed Deep Learning ROC Curve Ischemic Stroke Brain Ischemia Image Interpretation, Computer-Assisted Female Middle Cerebral Artery Aged Aged, 80 and over Male Middle Aged
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