AIMC Topic: Aged, 80 and over
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Pyramid feature adaptation for semi-supervised cardiac bi-ventricle segmentation.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 6, 2020
Cardiac bi-ventricle segmentation (BVS) is an essential task for assessing cardiac indices, such as the ejection fraction and volume of the left ventricle (LV) and right ventricle (RV). However, BVS is extremely challenging due to the high variabilit...
Predicting 10-Year Risk of End-Organ Complications of Type 2 Diabetes With and Without Metabolic Surgery: A Machine Learning Approach.
Diabetes care
Feb 6, 2020
OBJECTIVE: To construct and internally validate prediction models to estimate the risk of long-term end-organ complications and mortality in patients with type 2 diabetes and obesity that can be used to inform treatment decisions for patients and pra...
Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy.
Critical care (London, England)
Feb 6, 2020
BACKGROUND: Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Failure Assessment (SOFA) scoring systems do not adequately predict mortality of patients undergoing co...
Prospective and External Evaluation of a Machine Learning Model to Predict In-Hospital Mortality of Adults at Time of Admission.
JAMA network open
Feb 5, 2020
IMPORTANCE: The ability to accurately predict in-hospital mortality for patients at the time of admission could improve clinical and operational decision-making and outcomes. Few of the machine learning models that have been developed to predict in-h...
Radiomics for classification of bone mineral loss: A machine learning study.
Diagnostic and interventional imaging
Feb 4, 2020
PURPOSE: The purpose of this study was to develop predictive models to classify osteoporosis, osteopenia and normal patients using radiomics and machine learning approaches.
The application of artificial intelligence (AI) techniques to identify frailty within a residential aged care administrative data set.
International journal of medical informatics
Feb 4, 2020
INTRODUCTION: Research has shown that frailty, a geriatric syndrome associated with an increased risk of negative outcomes for older people, is highly prevalent among residents of residential aged care facilities (also called long term care facilitie...
Multiparametric radiomics methods for breast cancer tissue characterization using radiological imaging.
Breast cancer research and treatment
Feb 4, 2020
BACKGROUND AND PURPOSE: Multiparametric radiological imaging is vital for detection, characterization, and diagnosis of many different diseases. Radiomics provide quantitative metrics from radiological imaging that may infer potential biological mean...
Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone.
BMC medical informatics and decision making
Feb 3, 2020
BACKGROUND: Cardiovascular diseases kill approximately 17 million people globally every year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) occurs when the heart cannot pump enough blood to meet the needs of...
Real-time colorectal cancer diagnosis using PR-OCT with deep learning.
Theranostics
Feb 3, 2020
Prior reports have shown optical coherence tomography (OCT) can differentiate normal colonic mucosa from neoplasia, potentially offering an alternative technique to endoscopic biopsy - the current gold-standard colorectal cancer screening and surveil...
Deep Neural Networks for Chronological Age Estimation From OPG Images.
IEEE transactions on medical imaging
Jan 31, 2020
Chronological age estimation is crucial labour in many clinical procedures, where the teeth have proven to be one of the best estimators. Although some methods to estimate the age from tooth measurements in orthopantomogram (OPG) images have been dev...
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