AIMC Topic: Aged, 80 and over

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Machine Learning Algorithms Utilizing Functional Respiratory Imaging May Predict COPD Exacerbations.

Academic radiology Nov 23, 2018
RATIONALE AND OBJECTIVES: Acute chronic obstructive pulmonary disease exacerbations (AECOPD) have a significant negative impact on the quality of life and accelerate progression of the disease. Functional respiratory imaging (FRI) has the potential t...
Predictive Value of Tests Tidal Volume Airway Resistance Functional Residual Capacity Pulmonary Disease, Chronic Obstructive Male Middle Aged Disease Progression Support Vector Machine Humans Retrospective Studies Female Aged Aged, 80 and over
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The Sydney Triage to Admission Risk Tool (START2) using machine learning techniques to support disposition decision-making.

Emergency medicine Australasia : EMA Nov 23, 2018
OBJECTIVE: To further develop and refine an Emergency Department (ED) in-patient admission prediction model using machine learning techniques.
Triage Area Under Curve Emergency Service, Hospital Bayes Theorem Patient Admission Male Middle Aged Adolescent ROC Curve Logistic Models New South Wales Humans Machine Learning Forecasting Retrospective Studies Female Aged Aged, 80 and over Adult
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DeepSeeNet: A Deep Learning Model for Automated Classification of Patient-based Age-related Macular Degeneration Severity from Color Fundus Photographs.

Ophthalmology Nov 22, 2018
PURPOSE: In assessing the severity of age-related macular degeneration (AMD), the Age-Related Eye Disease Study (AREDS) Simplified Severity Scale predicts the risk of progression to late AMD. However, its manual use requires the time-consuming partic...
Photography Retinal Drusen Geographic Atrophy Diagnosis, Computer-Assisted Deep Learning Sensitivity and Specificity Models, Theoretical Area Under Curve Male Diagnostic Techniques, Ophthalmological Middle Aged Humans Disease Progression Severity of Illness Index Prospective Studies Female Reproducibility of Results Risk Factors Aged Aged, 80 and over
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Higher serum levels of fibroblast growth factor 21 in old patients with cachexia.

Nutrition (Burbank, Los Angeles County, Calif.) Nov 22, 2018
OBJECTIVE: Fibroblast growth factor (FGF)21 is promptly induced by short fasting in animal models to regulate glucose and fat metabolism. Data on FGF21 in humans are inconsistent and FGF21 has not yet been investigated in old patients with cachexia, ...
Fibroblast Growth Factors Endopeptidases Cachexia Cross-Sectional Studies Gelatinases Male Humans Serine Endopeptidases Pilot Projects Weight Loss Prospective Studies Membrane Proteins Female Aged Aged, 80 and over
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Disparities in the Treatment and Outcome of Stage I Non-Small-Cell Lung Cancer in the 21st Century.

Clinical lung cancer Nov 20, 2018
BACKGROUND: African American (AA) individuals are less likely to receive treatment and more likely to die from cancer compared with Caucasian (C) individuals. Recent advancements in surgery and radiation have improved outcomes in early stage non-smal...
Carcinoma, Non-Small-Cell Lung Neoplasm Staging Healthcare Disparities Survival Analysis History, 21st Century Middle Aged Lung Neoplasms United States Treatment Outcome Indians, North American Humans Black or African American Female Risk Factors Aged Aged, 80 and over Male
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Detection of Breast Cancer with Mammography: Effect of an Artificial Intelligence Support System.

Radiology Nov 20, 2018
Purpose To compare breast cancer detection performance of radiologists reading mammographic examinations unaided versus supported by an artificial intelligence (AI) system. Materials and Methods An enriched retrospective, fully crossed, multireader, ...
Humans Breast Neoplasms Artificial Intelligence Middle Aged Female ROC Curve Aged Mammography Aged, 80 and over Breast Adult Radiographic Image Enhancement
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Comparison of machine learning models for the prediction of mortality of patients with unplanned extubation in intensive care units.

Scientific reports Nov 20, 2018
Unplanned extubation (UE) can be associated with fatal outcome; however, an accurate model for predicting the mortality of UE patients in intensive care units (ICU) is lacking. Therefore, we aim to compare the performances of various machine learning...
Aged Aged, 80 and over Male Middle Aged Hospital Mortality ROC Curve Humans Machine Learning Intensive Care Units Female Glasgow Coma Scale Logistic Models Support Vector Machine Taiwan APACHE Airway Extubation
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Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.

PLoS medicine Nov 20, 2018
BACKGROUND: Emergency admissions are a major source of healthcare spending. We aimed to derive, validate, and compare conventional and machine learning models for prediction of the first emergency admission. Machine learning methods are capable of ca...
Data Mining Reproducibility of Results Risk Factors Sex Factors Aged Health Services Needs and Demand Aged, 80 and over Patient Admission Young Adult Needs Assessment Adult Male Time Factors Middle Aged Socioeconomic Factors Risk Assessment Health Status England Age Factors Adolescent Humans Emergency Service, Hospital Machine Learning Electronic Health Records Female
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Measurement and immunophenotyping of pleural fluid EpCAM-positive cells and clusters for the management of non-small cell lung cancer patients.

Lung cancer (Amsterdam, Netherlands) Nov 19, 2018
OBJECTIVES: A malignant pleural effusion (MPE) is a common complication in non-small cell lung cancer (NSCLC) with important staging and prognostic information. Patients with MPEs are often candidates for advanced therapies, however, the current gold...
Aged Pleural Effusion, Malignant Epithelial Cell Adhesion Molecule Aged, 80 and over Pleural Cavity Adult Male Lung Neoplasms Middle Aged B7-H1 Antigen Cohort Studies Carcinoma, Non-Small-Cell Lung Humans Immunophenotyping Prospective Studies Feasibility Studies Prognosis Female
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Automated detection of imaging features of disproportionately enlarged subarachnoid space hydrocephalus using machine learning methods.

NeuroImage. Clinical Nov 19, 2018
OBJECTIVE: Create an automated classifier for imaging characteristics of disproportionately enlarged subarachnoid space hydrocephalus (DESH), a neuroimaging phenotype of idiopathic normal pressure hydrocephalus (iNPH).
Brain Female Aged Aged, 80 and over Sensitivity and Specificity Male ROC Curve Support Vector Machine Magnetic Resonance Imaging Hydrocephalus, Normal Pressure Subarachnoid Space Humans Machine Learning
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