AIMC Topic: Aged, 80 and over

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Validation of a Machine Learning Model That Outperforms Clinical Risk Scoring Systems for Upper Gastrointestinal Bleeding.

Gastroenterology Sep 25, 2019
BACKGROUND & AIMS: Scoring systems are suboptimal for determining risk in patients with upper gastrointestinal bleeding (UGIB); these might be improved by a machine learning model. We used machine learning to develop a model to calculate the risk of ...
ROC Curve Blood Transfusion Emergency Service, Hospital Models, Biological Gastrointestinal Hemorrhage Humans Aged, 80 and over Adult Male Machine Learning Middle Aged Prognosis Risk Assessment Female Aged Hemostatic Techniques
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Radiologic-Radiomic Machine Learning Models for Differentiation of Benign and Malignant Solid Renal Masses: Comparison With Expert-Level Radiologists.

AJR. American journal of roentgenology Sep 25, 2019
The objective of our study was to compare the performance of radiologicradiomic machine learning (ML) models and expert-level radiologists for differentiation of benign and malignant solid renal masses using contrast-enhanced CT examinations. This ...
Female Aged Aged, 80 and over Young Adult Adult Male Middle Aged Clinical Competence Models, Theoretical Kidney Diseases Magnetic Resonance Imaging Diagnosis, Differential Radiology Kidney Neoplasms Humans Machine Learning Retrospective Studies Tomography, X-Ray Computed
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Prediction of complication related death after radical cystectomy for bladder cancer with machine learning methodology.

Scandinavian journal of urology Sep 25, 2019
To create a pre-operatively usable tool to identify patients at high risk of early death (within 90 days post-operatively) after radical cystectomy and to assess potential risk factors for post-operative and surgery related mortality. Material consi...
Aged Machine Learning Prognosis Aged, 80 and over Humans Retrospective Studies Postoperative Complications Male Female Urinary Bladder Neoplasms Middle Aged Risk Factors Cystectomy Risk Assessment
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Multi-Objective Optimization for Personalized Prediction of Venous Thromboembolism in Ovarian Cancer Patients.

IEEE journal of biomedical and health informatics Sep 24, 2019
Thrombotic events are one of the leading causes of mortality and morbidity related to cancer, with ovarian cancer having one of the highest incidence rates. The need to prevent these events through the prescription of adequate schemes of antithrombot...
Venous Thromboembolism Adult Middle Aged Risk Assessment Models, Statistical Ovarian Neoplasms Biomarkers Humans Precision Medicine Machine Learning Female Algorithms Aged Databases, Factual Aged, 80 and over
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Evaluating the performance of a predictive modeling approach to identifying members at high-risk of hospitalization.

Journal of medical economics Sep 24, 2019
To evaluate the risk-of-hospitalization (ROH) models developed at Blue Cross Blue Shield of Louisiana (BCBSLA) and compare this approach to the DxCG risk-score algorithms utilized by many health plans. Time zero for this study was December 31, 2016....
Insurance, Health Insurance Claim Review Child Logistic Models Residence Characteristics Models, Statistical Insurance Carriers Aged Aged, 80 and over Young Adult Adult Male Middle Aged Risk Assessment Infant Adolescent Child, Preschool Machine Learning Humans Algorithms Female Infant, Newborn Hospitalization
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Detection of Hemodynamically Significant Coronary Stenosis: CT Myocardial Perfusion versus Machine Learning CT Fractional Flow Reserve.

Radiology Sep 24, 2019
Background Direct intraindividual comparison of dynamic CT myocardial perfusion imaging (MPI) and machine learning (ML)-based CT fractional flow reserve (FFR) has not been explored for diagnosing hemodynamically significant coronary artery disease. P...
ROC Curve Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Sensitivity and Specificity Male Middle Aged Severity of Illness Index Hemodynamics Humans Tomography, X-Ray Computed Machine Learning Female Prospective Studies Aged Aged, 80 and over Adult
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Using path signatures to predict a diagnosis of Alzheimer's disease.

PloS one Sep 19, 2019
The path signature is a means of feature generation that can encode nonlinear interactions in data in addition to the usual linear terms. It provides interpretable features and its output is a fixed length vector irrespective of the number of input p...
Cognitive Dysfunction Aged, 80 and over Models, Theoretical Humans Male Magnetic Resonance Imaging Machine Learning Middle Aged Alzheimer Disease Brain Disease Progression Neuroimaging Female Case-Control Studies Aged
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Machine Learning to Predict In-Hospital Morbidity and Mortality after Traumatic Brain Injury.

Journal of neurotrauma Sep 18, 2019
Recently, successful predictions using machine learning (ML) algorithms have been reported in various fields. However, in traumatic brain injury (TBI) cohorts, few studies have examined modern ML algorithms. To develop a simple ML model for TBI outco...
Humans Machine Learning Prognosis Male Middle Aged Adolescent Child Hospital Mortality Brain Injuries, Traumatic Female Aged Aged, 80 and over Young Adult Adult
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Automated vertebrae localization and identification by decision forests and image-based refinement on real-world CT data.

La Radiologia medica Sep 14, 2019
PURPOSE: Development of a fully automatic algorithm for the automatic localization and identification of vertebral bodies in computed tomography (CT).
Decision Trees Anatomic Landmarks Spine Datasets as Topic Multidetector Computed Tomography Aged Aged, 80 and over Young Adult Adult Middle Aged Humans Machine Learning Algorithms Retrospective Studies
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Using supervised learning machine algorithm to identify future fallers based on gait patterns: A two-year longitudinal study.

Experimental gerontology Sep 11, 2019
INTRODUCTION: Given their major health consequences in the elderly, identifying people at risk of fall is a major challenge faced by clinicians. A lot of studies have confirmed the relationships between gait parameters and falls incidence. However, a...
Male Risk Assessment Pilot Projects Accidental Falls Longitudinal Studies Postural Balance Humans Algorithms Female Aged Aged, 80 and over Walking Gait Supervised Machine Learning Independent Living
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