AIMC Topic: Aged, 80 and over

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Forewarning of hypotensive events using a Bayesian artificial neural network in neurocritical care.

Journal of clinical monitoring and computing May 24, 2018
Traumatically brain injured (TBI) patients are at risk from secondary insults. Arterial hypotension, critically low blood pressure, is one of the most dangerous secondary insults and is related to poor outcome in patients. The overall aim of this stu...
Humans Neural Networks, Computer Machine Learning Software Databases, Factual Prospective Studies Intensive Care Units Female Critical Care Male Aged False Positive Reactions Brain Injuries Middle Aged Aged, 80 and over Area Under Curve Diagnosis, Computer-Assisted Young Adult Sample Size Pilot Projects Adult Bayes Theorem Adolescent Sensitivity and Specificity Signal Processing, Computer-Assisted Brain Injuries, Traumatic Hypotension
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Distinguishing True Progression From Radionecrosis After Stereotactic Radiation Therapy for Brain Metastases With Machine Learning and Radiomics.

International journal of radiation oncology, biology, physics May 24, 2018
PURPOSE: Treatment effect or radiation necrosis after stereotactic radiosurgery (SRS) for brain metastases is a common phenomenon often indistinguishable from true progression. Radiomics is an emerging field that promises to improve on conventional i...
Diagnosis, Differential Radiosurgery Radiation Injuries Aged, 80 and over Adult Brain Neoplasms Middle Aged Disease Progression Magnetic Resonance Imaging Humans Machine Learning Aged
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Integrating spatial-anatomical regularization and structure sparsity into SVM: Improving interpretation of Alzheimer's disease classification.

NeuroImage May 23, 2018
In recent years, machine learning approaches have been successfully applied to the field of neuroimaging for classification and regression tasks. However, many approaches do not give an intuitive relation between the raw features and the diagnosis. T...
Brain Mapping Alzheimer Disease Image Interpretation, Computer-Assisted Female Aged Aged, 80 and over Male Middle Aged Support Vector Machine Humans Brain
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A comparison of statistical and machine-learning techniques in evaluating the association between dietary patterns and 10-year cardiometabolic risk (2002-2012): the ATTICA study.

The British journal of nutrition May 23, 2018
Statistical methods are usually applied in examining diet-disease associations, whereas factor analysis is commonly used for dietary pattern recognition. Recently, machine learning (ML) has been also proposed as an alternative technique in health cla...
Hypercholesterolemia Adolescent Incidence Hypertension Diabetes Mellitus Adult Follow-Up Studies Male Reproducibility of Results Models, Statistical Cardiovascular Diseases Risk Factors Blood Pressure Middle Aged Humans Aged Data Interpretation, Statistical Diet Machine Learning Aged, 80 and over Sex Factors Risk Assessment Prospective Studies Young Adult Linear Models Female Pattern Recognition, Automated
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Statistical machine learning of sleep and physical activity phenotypes from sensor data in 96,220 UK Biobank participants.

Scientific reports May 21, 2018
Current public health guidelines on physical activity and sleep duration are limited by a reliance on subjective self-reported evidence. Using data from simple wrist-worn activity monitors, we developed a tailored machine learning model, using balanc...
Aged Aged, 80 and over Young Adult Adult Male Middle Aged Humans Machine Learning Phenotype Female United Kingdom Accelerometry Sedentary Behavior Exercise Adolescent Self Report Biological Specimen Banks Activities of Daily Living Sleep
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Factors associated with dementia in elderly.

Ciencia & saude coletiva May 18, 2018
We analyzed the factors associated with dementia in the elderly attended at a memory outpatient clinic of the University of Southern Santa Catarina (UNISUL). This is a cross-sectional study with data analysis of medical records from January 2013 to A...
Dementia Cross-Sectional Studies Humans Male Outpatient Clinics, Hospital Female Middle Aged Risk Factors Brazil Aged Diabetes Mellitus, Type 2 Prevalence Aged, 80 and over Depression Hypertension Vitamin D Memory Disorders
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Assessment of the generalization of learned image reconstruction and the potential for transfer learning.

Magnetic resonance in medicine May 17, 2018
PURPOSE: Although deep learning has shown great promise for MR image reconstruction, an open question regarding the success of this approach is the robustness in the case of deviations between training and test data. The goal of this study is to asse...
Humans Algorithms Databases, Factual Female Aged Aged, 80 and over Image Processing, Computer-Assisted Contrast Media Magnetic Resonance Imaging Models, Statistical Young Adult Signal-To-Noise Ratio Adult Protons Male Middle Aged Deep Learning Adolescent
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A Novel Deep Learning Approach for Automated Diagnosis of Acute Ischemic Infarction on Computed Tomography.

JACC. Cardiovascular imaging May 16, 2018
Deep Learning Predictive Value of Tests Acute Disease Radiographic Image Interpretation, Computer-Assisted Brain Infarction Humans Prospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Aged Aged, 80 and over Male Middle Aged
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Automated and real-time segmentation of suspicious breast masses using convolutional neural network.

PloS one May 16, 2018
In this work, a computer-aided tool for detection was developed to segment breast masses from clinical ultrasound (US) scans. The underlying Multi U-net algorithm is based on convolutional neural networks. Under the Mayo Clinic Institutional Review B...
Middle Aged Image Processing, Computer-Assisted Mammography Ultrasonography, Mammary Breast Humans Pattern Recognition, Automated Aged Carcinoma, Intraductal, Noninfiltrating Neural Networks, Computer Carcinoma, Ductal, Breast Aged, 80 and over Algorithms Carcinoma, Lobular Young Adult Prospective Studies Adult Female Breast Neoplasms
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Deep learning strategy for accurate carotid intima-media thickness measurement: An ultrasound study on Japanese diabetic cohort.

Computers in biology and medicine May 12, 2018
MOTIVATION: The carotid intima-media thickness (cIMT) is an important biomarker for cardiovascular diseases and stroke monitoring. This study presents an intelligence-based, novel, robust, and clinically-strong strategy that uses a combination of dee...
Humans Databases, Factual Female Diabetes Complications Aged Ultrasonography Carotid Artery Diseases ROC Curve Aged, 80 and over Japan Image Interpretation, Computer-Assisted Male Carotid Intima-Media Thickness Deep Learning Carotid Arteries Cohort Studies
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