AIMC Topic: Aged

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Deep Learning for Medication Assessment of Individuals with Parkinson's Disease Using Wearable Sensors.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Motor fluctuations between "OFF" state (with no benefit from medication) and " ON" state (with optimum benefit from medication) are a major focus of clinical managements in individuals with mid-stage and advance Parkinson's disease (PD). In this work...
Algorithms Aged Adult Middle Aged Deep Learning Wearable Electronic Devices Parkinson Disease Activities of Daily Living Humans
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Applying Machine-Learning Techniques to Build Self-reported Depression Prediction Models.

Computers, informatics, nursing : CIN Jul 1, 2018
Datasets as Topic Middle Aged Depression Logistic Models Mass Screening Self Report Female Aged Aged, 80 and over Male Humans Machine Learning
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Deep-learning Classifier With an Ultrawide-field Scanning Laser Ophthalmoscope Detects Glaucoma Visual Field Severity.

Journal of glaucoma Jul 1, 2018
PURPOSE: To evaluate the accuracy of detecting glaucoma visual field defect severity using deep-learning (DL) classifier with an ultrawide-field scanning laser ophthalmoscope.
Severity of Illness Index Deep Learning Microscopy, Confocal Vision Disorders Image Interpretation, Computer-Assisted Cross-Sectional Studies Intraocular Pressure Male Middle Aged Visual Fields Visual Field Tests Ophthalmoscopes Humans Glaucoma Retrospective Studies Female Reproducibility of Results Aged Adult Sensitivity and Specificity
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Inclusion of Unstructured Clinical Text Improves Early Prediction of Death or Prolonged ICU Stay.

Critical care medicine Jul 1, 2018
OBJECTIVES: Early prediction of undesired outcomes among newly hospitalized patients could improve patient triage and prompt conversations about patients' goals of care. We evaluated the performance of logistic regression, gradient boosting machine, ...
Decision Support Techniques Retrospective Studies Intensive Care Units Female Aged Humans Machine Learning Natural Language Processing Male Patient Care Planning Middle Aged Length of Stay Hospital Mortality
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Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity: The Mobile Parkinson Disease Score.

JAMA neurology Jul 1, 2018
IMPORTANCE: Current Parkinson disease (PD) measures are subjective, rater-dependent, and assessed in clinic. Smartphones can measure PD features, yet no smartphone-derived rating score exists to assess motor symptom severity in real-world settings.
Gait Analysis Voice Dopamine Agents Aged Male Humans Mobile Applications Middle Aged Machine Learning Parkinson Disease Severity of Illness Index Female Postural Balance Smartphone Reaction Time Gait
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Improving Hip-Worn Accelerometer Estimates of Sitting Using Machine Learning Methods.

Medicine and science in sports and exercise Jul 1, 2018
PURPOSE: This study aimed to improve estimates of sitting time from hip-worn accelerometers used in large cohort studies by using machine learning methods developed on free-living activPAL data.
Machine Learning Algorithms Female Aged Breast Neoplasms Humans Monitoring, Ambulatory Accelerometry Cross-Sectional Studies Sitting Position Middle Aged Hip Exercise Survivors Pilot Projects Thigh
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Renal Function Estimates and Dosing of Direct Oral Anticoagulants in Stroke Patients with Atrial Fibrillation: An Observational Study.

Acta neurologica Taiwanica Jun 15, 2018
PURPOSE: Appropriate dosing of direct oral anticoagulants (DOACs) requires consideration of renal function. Discordance between commonly used estimated glomerular filtration rate (eGFR) and creatinine clearance (CrCl) might affect the dosing appropri...
Anticoagulants Stroke Atrial Fibrillation Humans Dabigatran Rivaroxaban Aged Aged, 80 and over Middle Aged
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Deep Learning for Predicting Refractive Error From Retinal Fundus Images.

Investigative ophthalmology & visual science Jun 1, 2018
PURPOSE: We evaluate how deep learning can be applied to extract novel information such as refractive error from retinal fundus imaging.
Visual Fields Vision Tests Deep Learning Fundus Oculi Humans Retina Algorithms Datasets as Topic Adult Female Male Aged Middle Aged Refraction, Ocular Refractive Errors
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Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE Consortium.

Circulation. Cardiovascular imaging Jun 1, 2018
BACKGROUND: Coronary computed tomographic angiography (CTA) is a reliable modality to detect coronary artery disease. However, CTA generally overestimates stenosis severity compared with invasive angiography, and angiographic stenosis does not necess...
Humans Prospective Studies Retrospective Studies Asia Computed Tomography Angiography Severity of Illness Index Coronary Stenosis Deep Learning Fractional Flow Reserve, Myocardial United States Europe Female Predictive Value of Tests Reproducibility of Results Aged Male Middle Aged Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Coronary Vessels
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Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.

Investigative ophthalmology & visual science Jun 1, 2018
PURPOSE: To apply computational techniques to wide-angle swept-source optical coherence tomography (SS-OCT) images to identify novel, glaucoma-related structural features and improve detection of glaucoma and prediction of future glaucomatous progres...
Retrospective Studies Female Aged Adult Intraocular Pressure Male Middle Aged Disease Progression Unsupervised Machine Learning Visual Field Tests Optic Nerve Diseases Glaucoma, Open-Angle Tomography, Optical Coherence Tonometry, Ocular Humans Nerve Fibers Optic Disk Retinal Ganglion Cells Principal Component Analysis
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