AIMC Topic: Aged, 80 and over

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Using Machine Learning to Predict Rehabilitation Outcomes in Postacute Hip Fracture Patients.

Archives of physical medicine and rehabilitation Sep 16, 2020
OBJECTIVE: To use machine learning-based methods in designing a predictive model of rehabilitation outcomes for postacute hip fracture patients.
Subacute Care Humans Machine Learning Retrospective Studies Disability Evaluation Female Geriatric Assessment Aged Hip Fractures Physical Therapy Modalities Rehabilitation Centers Aged, 80 and over Male Surveys and Questionnaires Treatment Outcome Occupational Therapy
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Automatic Grading of Stroke Symptoms for Rapid Assessment Using Optimized Machine Learning and 4-Limb Kinematics: Clinical Validation Study.

Journal of medical Internet research Sep 16, 2020
BACKGROUND: Subtle abnormal motor signs are indications of serious neurological diseases. Although neurological deficits require fast initiation of treatment in a restricted time, it is difficult for nonspecialists to detect and objectively assess th...
Humans Machine Learning Algorithms Male Female Middle Aged Aged Stroke Aged, 80 and over Neurologic Examination Adult Biomechanical Phenomena
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Development of Machine Learning Models to Validate a Medication Regimen Complexity Scoring Tool for Critically Ill Patients.

The Annals of pharmacotherapy Sep 15, 2020
INTRODUCTION: The Medication Regimen Complexity -Intensive Care Unit (MRC-ICU) is the first tool for measuring medication regimen complexity in critically ill patients. This study tested machine learning (ML) models to investigate the relationship be...
Humans Machine Learning Retrospective Studies Critical Illness Intensive Care Units Male Female Middle Aged Hospitalization Hospital Mortality Aged Bayes Theorem Aged, 80 and over APACHE Adult Medication Reconciliation
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Usefulness of Semisupervised Machine-Learning-Based Phenogrouping to Improve Risk Assessment for Patients Undergoing Transcatheter Aortic Valve Implantation.

The American journal of cardiology Sep 15, 2020
Semisupervised machine-learning methods are able to learn from fewer labeled patient data. We illustrate the potential use of a semisupervised automated machine-learning (AutoML) pipeline for phenotyping patients who underwent transcatheter aortic va...
Treatment Outcome Aortic Valve Stenosis Transcatheter Aortic Valve Replacement Aged, 80 and over Male Humans Risk Assessment Machine Learning Severity of Illness Index Phenotype Cohort Studies Female Aged
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Automatic detection of non-perfusion areas in diabetic macular edema from fundus fluorescein angiography for decision making using deep learning.

Scientific reports Sep 15, 2020
Vision loss caused by diabetic macular edema (DME) can be prevented by early detection and laser photocoagulation. As there is no comprehensive detection technique to recognize NPA, we proposed an automatic detection method of NPA on fundus fluoresce...
Follow-Up Studies Decision Making Fundus Oculi Macular Edema Image Interpretation, Computer-Assisted Fluorescein Angiography Aged, 80 and over Adult Male Middle Aged Humans Neural Networks, Computer Diagnosis, Computer-Assisted Diabetic Retinopathy Deep Learning Algorithms Prognosis Female Aged
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The Brain Chart of Aging: Machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans.

Alzheimer's & dementia : the journal of the Alzheimer's Association Sep 13, 2020
INTRODUCTION: Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging d...
Amyloid beta-Peptides Middle Aged White Matter Humans Disease Progression Machine Learning Neuropsychological Tests Cognitive Dysfunction Biomarkers Atrophy Image Processing, Computer-Assisted Aged Brain Cerebral Small Vessel Diseases Magnetic Resonance Imaging Aged, 80 and over Female Young Adult Adult Male Aging
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Efficacy of endoscopic ultrasound with artificial intelligence for the diagnosis of gastrointestinal stromal tumors.

Journal of gastroenterology Sep 11, 2020
BACKGROUND: Although endoscopic ultrasound (EUS) is reported to be suitable for determining the layer from which subepithelial lesions (SELs) originate, it is difficult to distinguish gastrointestinal stromal tumor (GIST) from non-GIST using only EUS...
Pilot Projects Gastrointestinal Neoplasms Endosonography Gastrointestinal Stromal Tumors Humans Artificial Intelligence Retrospective Studies Female Aged Aged, 80 and over Young Adult Adult Sensitivity and Specificity Male Middle Aged
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Deep Learning and Multivariable Models Select EVAR Patients for Short-Stay Discharge.

Vascular and endovascular surgery Sep 10, 2020
OBJECTIVES: We sought to develop a prediction score with data from the Vascular Quality Initiative (VQI) EVAR in efforts to assist endovascular specialists in deciding whether or not a patient is appropriate for short-stay discharge.
Decision Support Techniques Databases, Factual Clinical Decision-Making Female Risk Factors Aged Humans Time Factors Smartphone Mobile Applications Treatment Outcome Patient Discharge Patient Selection Aged, 80 and over Male Risk Assessment Deep Learning Length of Stay Multivariate Analysis Endovascular Procedures Enhanced Recovery After Surgery Health Services Research Aortic Aneurysm
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A Comparative Analysis of Two Machine Learning-Based Diagnostic Patterns with Thyroid Imaging Reporting and Data System for Thyroid Nodules: Diagnostic Performance and Unnecessary Biopsy Rate.

Thyroid : official journal of the American Thyroid Association Sep 9, 2020
The risk stratification system of the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) for thyroid nodules is affected by low diagnostic specificity. Machine learning (ML) methods can optimize the diagnostic perf...
Aged Aged, 80 and over Young Adult Adult Male Middle Aged Machine Learning Retrospective Studies Clinical Decision-Making Female Reproducibility of Results China Adolescent Predictive Value of Tests Thyroid Neoplasms Tumor Burden Humans Ultrasonography Image Interpretation, Computer-Assisted Thyroid Nodule Biopsy, Fine-Needle Unnecessary Procedures Elasticity Imaging Techniques
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Artificial Intelligence Predictive Analytics in the Management of Outpatient MRI Appointment No-Shows.

AJR. American journal of roentgenology Sep 9, 2020
Outpatient appointment no-shows are a common problem. Artificial intelligence predictive analytics can potentially facilitate targeted interventions to improve efficiency. We describe a quality improvement project that uses machine learning techniqu...
Aged, 80 and over Young Adult Humans Adolescent Adult Machine Learning Child Male Forecasting Magnetic Resonance Imaging Middle Aged Prospective Studies Ambulatory Care Female No-Show Patients Aged
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